ORCID Profile
0000-0002-1733-5988
Current Organisations
University of Tehran
,
Universitas Pendidikan Indonesia
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Publisher: Springer Science and Business Media LLC
Date: 10-11-2020
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 04-2009
Publisher: Springer Science and Business Media LLC
Date: 31-03-2021
Publisher: IEEE
Date: 07-2009
Publisher: Springer Science and Business Media LLC
Date: 09-03-2020
Publisher: IEEE
Date: 12-2008
Publisher: IEEE
Date: 04-2011
Publisher: Elsevier BV
Date: 12-2014
Publisher: IEEE
Date: 12-2018
Publisher: Elsevier BV
Date: 04-2017
Publisher: Inderscience Publishers
Date: 2018
Publisher: Informa UK Limited
Date: 17-08-2020
Publisher: Elsevier BV
Date: 08-2009
Publisher: IEEE
Date: 12-2016
Publisher: Informa UK Limited
Date: 12-05-2020
Publisher: Elsevier BV
Date: 12-2009
Publisher: Springer Science and Business Media LLC
Date: 14-11-2014
Publisher: Springer Science and Business Media LLC
Date: 18-12-2014
Publisher: Production Engineering Institute (PEI), Faculty of Mechanical Engineering
Date: 23-03-2019
Publisher: Emerald
Date: 06-06-2020
DOI: 10.1108/JEIM-09-2019-0282
Abstract: Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately. In this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods. To show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment. To the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.
Publisher: Elsevier BV
Date: 07-2010
Publisher: Elsevier BV
Date: 2008
Publisher: IEEE
Date: 09-2012
Publisher: Springer Science and Business Media LLC
Date: 11-10-2018
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 2013
Publisher: Elsevier BV
Date: 04-2016
Publisher: Elsevier BV
Date: 10-2014
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11571155_18
Publisher: Elsevier BV
Date: 08-2023
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 2018
Publisher: Growing Science
Date: 04-2013
Publisher: Informa UK Limited
Date: 05-09-2014
Publisher: Elsevier BV
Date: 12-2014
Publisher: IEEE
Date: 12-2011
Publisher: Elsevier BV
Date: 02-2018
Publisher: Elsevier BV
Date: 02-2019
Publisher: American Chemical Society (ACS)
Date: 23-02-2023
Publisher: IEEE
Date: 12-2011
Publisher: Hindawi Limited
Date: 2014
DOI: 10.1155/2014/214615
Abstract: This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.
Publisher: Elsevier BV
Date: 08-2005
Publisher: SAGE Publications
Date: 09-2018
Abstract: This article formulates the operating rooms considering several constraints of the real world, such as decision-making styles, multiple stages for surgeries, time windows for resources, and specialty and complexity of surgery. Based on planning, surgeries are assigned to the working days. Then, the scheduling part determines the sequence of surgeries per day. Moreover, an integrated fuzzy possibilistic–stochastic mathematical programming approach is applied to consider some sources of uncertainty, simultaneously. Net revenues of operating rooms are maximized through the first objective function. Minimizing a decision-making style inconsistency among human resources and maximizing utilization of operating rooms are considered as the second and third objectives, respectively. Two popular multi-objective meta-heuristic algorithms including Non-dominated Sorting Genetic Algorithm and Multi-Objective Particle Swarm Optimization are utilized for solving the developed model. Moreover, different comparison metrics are applied to compare the two proposed meta-heuristics. Several test problems based on the data obtained from a public hospital located in Iran are used to display the performance of the model. According to the results, Non-dominated Sorting Genetic Algorithm-II outperforms the Multi-Objective Particle Swarm Optimization algorithm in most of the utilized metrics. Moreover, the results indicate that our proposed model is more effective and efficient to schedule and plan surgeries and assign resources than manual scheduling.
Publisher: Informa UK Limited
Date: 21-05-2014
Publisher: Elsevier BV
Date: 11-2012
Publisher: Springer Science and Business Media LLC
Date: 11-04-2013
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier
Date: 2018
Publisher: Informa UK Limited
Date: 10-09-2014
Publisher: Informa UK Limited
Date: 05-02-2015
Publisher: IEEE
Date: 12-2014
Publisher: Elsevier BV
Date: 05-2010
Publisher: Elsevier BV
Date: 2018
Publisher: IEEE
Date: 04-2018
Publisher: Elsevier BV
Date: 2007
Publisher: AIP Publishing
Date: 10-07-2006
DOI: 10.1063/1.2210080
Abstract: We report on the synthesis of La0.7Sr0.3MnO3 (LSMO) nanoparticles having perovskite structure and particle size of the order of 30nm. The process involves citrate-gel synthesis, size filtering, and surface coating with a shell of octadecyl amine (ODA) using electrostatic interaction-assisted novel chemical route. Magnetic measurements show the Curie temperature of ∼360K establishing the desired stoichiometry and phase. Fourier transform infrared studies bring out that the amine group of ODA interacts with the LSMO surface. Refluidization yields uniform redispersion of the coated and dried powder.
Publisher: Springer Science and Business Media LLC
Date: 02-09-2009
Publisher: Springer Science and Business Media LLC
Date: 08-07-2009
Publisher: Growing Science
Date: 10-2012
Publisher: Elsevier BV
Date: 2013
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 11-2019
Publisher: Informa UK Limited
Date: 15-07-2020
Publisher: IEEE
Date: 09-2019
Publisher: Elsevier BV
Date: 06-2005
Publisher: Inderscience Publishers
Date: 2015
Publisher: SAGE Publications
Date: 22-11-2020
Abstract: Assigning nurses to appropriate departments and work shifts based on human factors can strengthen teamwork and boost the efficiency of healthcare systems. The human factors considered in this study include skill, preference, and compatibility of nurses. In this regard, a unique multi-objective mathematical model for nurse scheduling is proposed in this article, in which nurses’ decision-making styles are taken into account. Three objectives, including minimization of the total cost of staffing, minimization of the sum of incompatibility among nurses’ decision-making styles assigned to the same shift days, and maximization of the overall satisfaction of nurses for their assigned shifts, are addressed in this model. Three meta-heuristics, namely, multi-objective Keshtel algorithm, non-dominated sorting genetic algorithm II, and multi-objective tabu search, are developed to solve the problem. Moreover, a data envelopment analysis method is employed to rank the obtained Pareto solutions. Afterwards, a real-life case at a large hospital in Tehran, Iran, is investigated. Eventually, the applicability and effectiveness of the proposed model are assessed based on the experimental results.
Publisher: Elsevier BV
Date: 04-2008
Publisher: Elsevier BV
Date: 2019
Publisher: Informa UK Limited
Date: 10-03-2020
Publisher: Elsevier BV
Date: 08-2007
Publisher: MDPI AG
Date: 17-08-2017
DOI: 10.3390/SU9081433
Publisher: Elsevier BV
Date: 04-2014
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 07-2016
DOI: 10.1016/J.JCIN.2016.04.004
Abstract: The aim of this study was to compare the incidence and impact of cessation of dual-antiplatelet therapy (DAPT) in women and men treated with percutaneous coronary intervention. Nonadherence to cardiovascular medications and female sex are associated with worse outcomes. However, the patterns and impact of DAPT cessation in women compared with men following percutaneous coronary intervention have not been studied. Baseline characteristics, patterns of DAPT cessation, and 2-year clinical outcomes were compared in 5,031 patients (1,279 women, 3,739 men) enrolled following successful percutaneous coronary intervention with stents in the PARIS (Patterns of Non-Adherence to Antiplatelet Regimens in Stented Patients) study. DAPT cessation was adjudicated as physician-guided discontinuation, interruption for surgery, or disruption due to bleeding or noncompliance. Clinical endpoints were major adverse cardiac events (a composite of cardiac death, definite or probable stent thrombosis, spontaneous myocardial infarction, or clinically indicated target lesion revascularization), a second restricted definition of major adverse cardiac events excluding target lesion revascularization, and bleeding. DAPT cessation was more common in women than men (59.1% vs. 55.9%, p = 0.007) and comprised increased rates of discontinuation, disruption for bleeding, and disruption due to noncompliance. The impact of DAPT cessation was similar regardless of sex and varied according the mode in particular, disruption was associated with increased risk for both ischemic and bleeding events. After adjusting for differences in baseline and treatment characteristics as well as DAPT cessation events, female sex remained an independent predictor of bleeding but not of ischemic events. DAPT cessation was more common in women, but its impact was similar in women and men. Female sex was an independent predictor of bleeding but not of ischemic events after adjustment for differences in DAPT cessation and baseline and treatment characteristics.
Publisher: Informa UK Limited
Date: 30-03-2021
Publisher: Springer International Publishing
Date: 2021
Publisher: Growing Science
Date: 10-2011
Publisher: Informa UK Limited
Date: 18-10-2019
Publisher: SAGE Publications
Date: 30-04-2009
Abstract: This paper presents a novel mathematical model for a stochastic location-routing problem (SLRP) that minimizes the facilities establishing cost and transportation cost, and maximizes the probability of delivery to customers. In this proposed model, new aspects of a location-routing problem (LRP), such as stochastic availability of facilities and routes, are developed that are similar to real-word problems. The proposed model is solved in two stages: (i) solving the facility location problem (FLP) by a mathematical algorithm and (ii) solving the multi-objective multi-depot vehicle routing problem (MO-MDVRP) by a simulated annealing (SA) algorithm hybridized by genetic operators, namely mutation and crossover. The proposed SA can find good solutions in a reasonable time. It solves the proposed model in large-scale problems with acceptable results. Finally, a trade-off curve is used to depict and discuss a large-sized problem. The associated results are compared with the results obtained by the lower bound and Lingo 8.0 software.
Publisher: Inderscience Publishers
Date: 2018
Publisher: Informa UK Limited
Date: 09-02-2023
Publisher: Elsevier BV
Date: 04-2008
Publisher: Springer Science and Business Media LLC
Date: 05-11-2012
Publisher: Growing Science
Date: 07-2013
Publisher: SciTech Solutions
Date: 31-01-2019
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 05-2018
Publisher: Elsevier BV
Date: 06-2010
Publisher: Springer Science and Business Media LLC
Date: 09-04-2010
Publisher: Informa UK Limited
Date: 13-11-2016
Publisher: Mary Ann Liebert Inc
Date: 06-2011
Publisher: Elsevier BV
Date: 02-2008
Publisher: Elsevier BV
Date: 11-2012
Publisher: Springer Science and Business Media LLC
Date: 14-03-2012
Publisher: Informa UK Limited
Date: 07-2012
Publisher: Elsevier BV
Date: 11-2023
Publisher: Springer Science and Business Media LLC
Date: 24-05-2012
Publisher: World Scientific Pub Co Pte Lt
Date: 12-2009
DOI: 10.1142/S0218126609005885
Abstract: The electromagnetism-like method (EM) is a population based meta-heuristic algorithm utilizing an attraction-repulsion mechanism to move s le points (i.e., our solutions) towards the optimality. In general, the EM has been initially used for solving continuous optimization problems and could not be applied on combinatorial optimization ones. This paper proposes a discrete binary version of the EM for solving combinatorial optimization problems. To show the efficiency of our proposed EM, we solve a single machine scheduling problem and compare our computational results with the solutions reported in the literature. Finally, we conclude that our proposed method is capable of solving such well-known problems more efficiently than the previous studies.
Publisher: Informa UK Limited
Date: 15-10-2013
Publisher: Elsevier BV
Date: 10-2011
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Elsevier BV
Date: 05-2018
Publisher: IEEE
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 05-10-2013
Publisher: Springer Science and Business Media LLC
Date: 09-11-2018
Publisher: Informa UK Limited
Date: 25-09-2018
Publisher: Elsevier BV
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 28-03-2012
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 08-2019
Publisher: Informa UK Limited
Date: 18-11-2020
Publisher: IEEE
Date: 09-2008
DOI: 10.1109/HIS.2008.71
Publisher: Elsevier BV
Date: 2009
Publisher: Elsevier BV
Date: 05-2017
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 05-2015
Publisher: Informa UK Limited
Date: 07-04-2015
Publisher: Informa UK Limited
Date: 06-07-2021
Publisher: Elsevier BV
Date: 08-2016
Publisher: IEEE
Date: 07-2009
Publisher: IEEE
Date: 09-2019
Publisher: Elsevier BV
Date: 05-2011
Publisher: Inderscience Publishers
Date: 2019
Publisher: Hindawi Limited
Date: 2013
DOI: 10.1155/2013/375628
Abstract: This paper considers four types of the most prominent risks in the supply chain. Their subcriteria and relations between them and within the network are also considered. In a supply chain, risks are mostly created by fluctuations. The aim of this study is to adopt a strategy for eliminating or reducing risks in a supply chain network. Having various solutions helps the supply chain to be resilient. Therefore, five alternatives are considered, namely, total quality management (TQM), leanness, alignment, adaptability, and agility. This paper develops a new network of supply chain risks by considering the interactions between risks. Perhaps, the network elements have interacted with some or all of the factors (clusters) or subfactors. We constitute supply chain risks in the analytic network process (ANP), which attracted less attention in the previous studies. Most of the studies about making a decision in supply chains have been applied in analytic hierarchy process (AHP) network. The present study considers the ANP as a well-known multicriteria decision making (MCDM) technique to choose the best alternative, because of the interdependency and feedbacks of different levels of the network. Finally, the ANP selects TQM as the best alternative among the considered ones.
Publisher: Elsevier BV
Date: 12-2012
Publisher: Elsevier BV
Date: 04-2011
Publisher: Elsevier BV
Date: 10-2022
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 07-2020
Publisher: Inderscience Publishers
Date: 2014
Publisher: Emerald
Date: 21-06-2020
DOI: 10.1108/JHLSCM-11-2018-0072
Abstract: This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters). A shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used. The results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method. In this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model. The outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases. A novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.
Publisher: IEEE
Date: 08-2204
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 2019
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: IEEE
Date: 12-2008
Publisher: Elsevier BV
Date: 08-2009
Publisher: Informa UK Limited
Date: 02-01-2021
Publisher: Elsevier BV
Date: 02-2012
Publisher: Informa UK Limited
Date: 24-02-2022
Publisher: Springer Science and Business Media LLC
Date: 22-03-2013
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: Informa UK Limited
Date: 04-2008
Publisher: Informa UK Limited
Date: 18-12-2018
Publisher: Elsevier BV
Date: 05-2022
Publisher: Informa UK Limited
Date: 04-07-2023
Publisher: Elsevier BV
Date: 08-2023
Publisher: SAGE Publications
Date: 23-05-2013
Abstract: This article presents inspection scenarios for the multiobjective multiconstraint mixed backorder and lost sales inventory model with imperfect items in which the order quantity, reorder point, ordering cost, lead time, and backorder rate are decision variables. The objectives are minimizing expected annual cost and variance of shortages. The number of imperfect items is assumed to be a beta-binomial random variable. There are two inspection scenarios: the imperfect items observed during inspection and screenings are either all reworked or all discarded. In order to fit some real environment, this study assumes the maximum permissible storage space and available budget are limited. Backorder rate is considered as a function of expected shortages at the end of cycle. Stochastic inflationary conditions with a probability density function are also considered in the presented model. This study assumes that the purchasing cost is paid when an order arrives at the beginning of the cycle, and the ordering cost is paid at the time of the order placing. The aggregate demand follows a normal distribution function. Finally, a solution procedure is proposed in order to solve the discussed multiobjective model. In addition, a numerical ex le is presented to illustrate the multiobjective model and its solution procedure for different inspection scenarios, and a sensitivity analysis is conducted with respect to the important system parameters.
Publisher: Springer International Publishing
Date: 12-12-2018
Publisher: Wiley
Date: 29-04-2019
DOI: 10.1111/ITOR.12672
Publisher: Springer Science and Business Media LLC
Date: 02-10-2008
Publisher: Elsevier BV
Date: 15-03-2010
Publisher: Springer International Publishing
Date: 12-12-2019
Publisher: SAGE Publications
Date: 02-06-2020
Abstract: Disasters cause a huge number of injured patients in a short time while existing emergency facilities encountered devastation and cannot respond properly. Here, the importance of implementing temporary emergency management becomes clear. This study aims to locate some temporary emergency stations across the area by maximal covering after a disaster. Furthermore, a multi-mode fleet is used for transferring patients using different modes of transportation (e.g. helicopter ambulance and bus ambulance). Since the type of patients may change over periods, medical servers can displace among temporary emergency stations dynamically according to disaster severity. For this purpose, a new bi-objective dynamic location-helicopter ambulance allocation-ambulance routing model with multi-medical servers is presented. The first objective function minimizes the operational costs related to the newly designed Emergency Medical Service along with the rate of human loss. The second objective function minimizes the critical time spent before the medical treatment. To validate the developed model, the augmented ε-constraint method is used and applied for the Tehran city, which shows the applicability of the model. Finally, two meta-heuristic algorithms are customized for large-sized problems, and the related results are compared based on multi-objective algorithms’ performance comparison metrics to find the more efficient one.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 10-2023
Publisher: Elsevier BV
Date: 2018
Publisher: Informa UK Limited
Date: 19-10-2021
Publisher: Public Library of Science (PLoS)
Date: 27-03-2013
Publisher: Springer Science and Business Media LLC
Date: 04-08-2019
Publisher: Informa UK Limited
Date: 23-07-2014
Publisher: Elsevier BV
Date: 05-2018
DOI: 10.1016/J.ARTMED.2018.03.003
Abstract: Medication selection for Type 2 Diabetes (T2D) is a challenging medical decision-making problem involving multiple medications that can be prescribed to control the patient's blood glucose. The wide range of hyperglycemia lowering agents with varying effects and various side effects makes the decision quite difficult. This paper presents computer-aided medical decision support using a fuzzy Multi-Criteria Decision-Making (MCDM) model that hybridizes a Step-wise Weight Assessment Ratio Analysis (SWARA) method with a modification of Fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full multiplicative form (FMULTIMOORA) method for pharmacological therapy selection of T2D. It makes the use of SWARA for obtaining the relative significance of every selected criterion by soliciting experts' opinions and FMULTIMOORA method for evaluation of each alternative according to all criteria based on a published clinical guideline. In this paper, an extended reference point approach is considered in the proposed hybrid MCDM model that resolves the classic reference point limitations and improves the FMULTIMOORA ranking procedure. Computational results indicate that Metformin is confirmed as the first-line medication and Sulfonylurea as the second-line add-on therapy. The Glucagon-like peptide-1 receptor agonist, Dipeptidyl peptidase-4 inhibitor, and Insulin are placed 3rd, 4th, and 5th, respectively. A sensitivity analysis is conducted to validate the model performance by comparing its result with studies in the literature, other fuzzy MCDM techniques and an interval MULTIMOORA method based on an observational dataset. The close correspondence between the final rankings of anti-diabetic agents resulted from the proposed hybrid model and other methodologies provide significant implications for endocrinologists to refer.
Publisher: Informa UK Limited
Date: 18-11-2017
Publisher: Elsevier BV
Date: 04-2013
Publisher: Elsevier BV
Date: 2014
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 07-2020
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 07-2018
Publisher: Informa UK Limited
Date: 2008
Publisher: Informa UK Limited
Date: 06-2013
Publisher: Springer Science and Business Media LLC
Date: 11-02-2010
Publisher: Elsevier BV
Date: 06-2018
Publisher: Informa UK Limited
Date: 04-10-2013
Publisher: SciTech Solutions
Date: 03-03-2019
Publisher: Springer Science and Business Media LLC
Date: 26-06-2017
Publisher: Inderscience Publishers
Date: 2015
Publisher: Elsevier BV
Date: 03-2011
Publisher: EDP Sciences
Date: 2007
DOI: 10.1051/RO:2007005
Publisher: Springer Science and Business Media LLC
Date: 25-04-2013
Publisher: Springer Science and Business Media LLC
Date: 15-04-2023
Publisher: Elsevier BV
Date: 10-2006
Publisher: Elsevier BV
Date: 03-2023
Publisher: Springer Science and Business Media LLC
Date: 11-2012
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 11-07-2010
Publisher: Springer Science and Business Media LLC
Date: 02-06-2022
DOI: 10.1038/S41588-022-01072-5
Abstract: The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic in iduals ( n max = 12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic in iduals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic in iduals. Furthermore, in autistic in iduals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic in iduals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.
Publisher: IEEE
Date: 12-2011
Publisher: Informa UK Limited
Date: 18-04-2022
Publisher: MDPI AG
Date: 28-10-2022
DOI: 10.3390/SU142114075
Abstract: With the increase in pollutants, the need to use electric vehicles (EVs) in various urban logistics activities is an increasingly important issue. Currently, there are issues with the efficiency of transport companies in recognizing the effects of uncertain factors in daily logistics operations. Thus, this research proposes a novel fuzzy two-echelon vehicle routing problem involving heterogeneous fleet EVs and internal combustion vehicles (ICVs). The first echelon is recyclable wastes collected from waste pickup points and transported to the primary centers by EVs. The second echelon is transporting recyclable wastes to recycling centers by ICVs. In the proposed models, fuzzy numbers are used to express the rate and energy consumption depending on the amount of load, vehicle speed, and recyclable waste. In addition, a penalty cost of the time windows is considered in both echelons. The models are solved by CPLEX and two meta-heuristic algorithms, gray wolf optimizer (GWO) and tabu search (TS), based on different instance sizes. The results show the efficiency of the proposed algorithms.
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 11-2019
Publisher: Springer Science and Business Media LLC
Date: 11-01-2023
Publisher: MDPI AG
Date: 29-03-2022
DOI: 10.3390/BUILDINGS12040414
Abstract: This paper develops an integrated model for the distribution of post-disaster temporary shelters after a large-scale disaster. The proposed model clusters impacted areas using an Adaptive Neuro-Fuzzy Inference System (ANFIS) method and then prioritizes the points of clusters by affecting factors on the route reliability using a permanent matrix. The model’s objectives are to minimize the maximum service time, maximize the route reliability and minimize the unmet demand. In the case of ground relief, the possibility of a breakdown in the vehicle is considered. Due to the disaster’s uncertain nature, the demands of impacted areas are considered in the form of fuzzy numbers, and then the equivalent crisp counterpart of the non-deterministic is made by Jimenez’s method. Since the developed model is multi-objective, the Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Firefly Algorithm (MOFA) are applied to find efficient solutions. The results confirm higher accuracy and lower computational time of the proposed MOFA. The findings of this study can contribute to the growing body of knowledge about disaster management strategies and have implications for critical decision-makers involved in post-disaster response projects. Furthermore, this study provides valuable information for national decision-makers in countries with limited experience with disasters and where the destructive consequences of disasters on the built environment are increasing.
Publisher: EDP Sciences
Date: 18-12-2015
DOI: 10.1051/RO/2014031
Publisher: Springer Science and Business Media LLC
Date: 07-11-2015
Publisher: Springer Science and Business Media LLC
Date: 23-09-2022
Publisher: Elsevier BV
Date: 07-2022
Publisher: Elsevier BV
Date: 2013
Publisher: SAGE Publications
Date: 10-06-2019
Abstract: Type 2 diabetes has an increasing prevalence and high cost of treatment. The goal of type 2 diabetes treatment is to control patients’ blood glucose level by pharmacological interventions and to prevent adverse disease-related complications. Therefore, it is important to optimize the medication treatment plans for type 2 diabetes patients to enhance the quality of their lives and to decrease the economic burden of this chronic disease. Since the treatment of type 2 diabetes relies on medication, it is vital to consider adverse drug reactions. Adverse drug reaction is undesired harmful reactions that may result from some certain medications. Therefore, a Markov decision process is developed in this article to model the medication treatment of type 2 diabetes, considering the possibility of adverse drug reaction occurring adverse drug reaction. The optimal policy of the proposed Markov decision process model is compared with clinical guidelines and existing models in the literature. Moreover, a sensitivity analysis is conducted to address the manner in which model behavior depends on model parameterization and then therapeutic insights are obtained based on the results. The satisfying results show that the model has the capability to offer an optimal treatment policy with an acceptable expected quality of life by utilizing fewer medications and provide significant implications in endocrinology and metabolism applications.
Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 11-2018
Publisher: SAGE Publications
Date: 25-04-2021
DOI: 10.1177/00375497211006175
Abstract: In an emergency medical system, the locations of ambulance stations has a direct impact on response time. In this paper, two location models are presented in combination with the hypercube queuing model to maximize coverage probability. In the first model, the locations of free and busy ambulances are considered in the system states, and the hypercube model can be analyzed accurately. The model contains a large number of states, and cannot be used for large-sized problems. For this reason, the second model is presented with the same assumptions as in the first model, except that the locations of busy ambulances are not included in the system state, but approximated based on the arrival rates. Both models are offline and dynamic, in which an ambulance does not necessarily return to the station from which it has been dispatched. Two strategies are defined for returning ambulances to the stations from the customer’s location. In the first strategy, the ambulance is returned to the nearest station after completion of its mission, and in the second strategy, it returns to the empty station that covers the highest demand rate. For evaluation of the performance of the proposed models, small-sized ex les are solved for both return strategies using the GAMS software. A simulation-optimization approach combined with a simulated annealing algorithm and a discrete-event simulation are used for solving large-sized problems. Moreover, real data from a case study are used to demonstrate the performance of the models in the real world.
Publisher: Elsevier BV
Date: 04-2021
Publisher: IEEE
Date: 05-2011
Publisher: Elsevier BV
Date: 03-2015
Publisher: Springer Science and Business Media LLC
Date: 06-04-2012
Publisher: Springer Science and Business Media LLC
Date: 12-02-2022
Publisher: Elsevier BV
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 12-02-2010
Publisher: Springer Science and Business Media LLC
Date: 15-11-2009
Publisher: Elsevier BV
Date: 05-2011
Publisher: Springer Science and Business Media LLC
Date: 12-06-2022
Publisher: Springer Science and Business Media LLC
Date: 07-07-2018
Publisher: Emerald
Date: 11-04-2022
DOI: 10.1108/JAMR-08-2021-0285
Abstract: The purpose of this paper is to design petroleum products’ supply chain management, which includes efficient integration of suppliers, manufacturers, storehouses and retailers. This paper proposes that a three-level supply chain will be turned into a bi-level supply chain of petroleum products by simultaneous integration of the middle level with the upstream and downstream levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels. The concepts of the design, structure and outputs are led by the model's solution. The model also responds to the variations in the market via coordination in the related decisions to the distribution, production and inventory issues, and also coordinating between the demands and production. This paper has limited its analysis to definite values due to the over-expansion of calculations and analysis. Future works can study other aspects of the proposed model for a multi-level petroleum product supply chain in different states of certain parameters and time zones. The designed model can directly and transparently help the oil managers and decision-makers lower the costs of manufacturing, distribution and sales with respect to the determined criteria. This paper establishes that effectiveness of the dynamic petroleum materials supply chain design will increase by considering maintained and increased production costs and coordinate management flows at all levels by supply chain creation’s integration.
Publisher: Springer Science and Business Media LLC
Date: 08-09-2015
Publisher: Springer Science and Business Media LLC
Date: 15-05-2013
Publisher: Hindawi Limited
Date: 2013
DOI: 10.1155/2013/543940
Abstract: As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN), self-organizing maps (SOM), alpha-cut fuzzy c -means ( α -FCM), and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α -FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α -FCM + ANN + Cox model significantly performs better than the two other hierarchical models.
Publisher: Growing Science
Date: 2015
Publisher: SAGE Publications
Date: 05-02-2022
Abstract: The surge in competition among companies to acquire a more significant portion of the market as well as respecting customer preferences in high quality and erse products result in a reduction of product life cycles. Accordingly, companies are under enormous pressure to introduce new high quality and erse products on time. Assessing new product designs at the primary phases of new product development (NPD) is a necessary and complex activity that can considerably reduce the time and cost of introducing new products to the market. The current methods of evaluating new product conceptual designs, including employing decision-making methods based on subjective opinions of experts, utilizing simulation packages, and following trial-and-error approaches in prototyping, may be inefficient, very time-consuming, and costly. To overcome this issue, this paper develops a quantitative data-driven Multi-Criteria Decision-Making (MCDM) approach founded on the combination of an Artificial Neural Network (ANN) method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to assess the new conceptual designs. So that the ANN method is utilized to predict the performance characteristics of new designs based on the related existed data of similar products, and TOPSIS is employed to score and rank different proposed alternatives designs. Finally, a case study of evaluating new product conceptual designs in an automotive research and development company is considered to demonstrate the performance and applicability of the proposed approach.
Publisher: Springer Science and Business Media LLC
Date: 15-07-2013
Publisher: Wiley
Date: 04-05-2022
DOI: 10.1111/ITOR.12989
Abstract: A Markov decision process (MDP) is an appropriate mathematical framework for analysis and modeling a large class of sequential decision‐making problems. Real‐world applications necessitate the evaluation of the value of a decision according to several conflicting objectives. This paper presents an extended ϵ‐constraint method for a multiobjective finite‐horizon MDP. This study integrates the ϵ‐constraint method with the K‐ best policies algorithm to find the nondominated deterministic Markovian policies on the Pareto‐optimal frontier. The proposed algorithm is evaluated on biobjective maintenance scheduling and machine running speed selection problems, and its performance is compared with a classic approach in the literature (weighted‐sum, WS, method). Satisfying results show that the proposed algorithm obtains a good‐quality Pareto frontier and has advantages over the WS method.
Publisher: Informa UK Limited
Date: 14-10-2019
Publisher: IEEE
Date: 12-2010
Publisher: IEEE
Date: 12-2019
Publisher: Springer International Publishing
Date: 2021
Publisher: Informa UK Limited
Date: 11-08-2017
Publisher: Elsevier BV
Date: 12-2013
Publisher: IEEE
Date: 12-2019
Publisher: Springer Science and Business Media LLC
Date: 22-09-2020
Publisher: Springer Science and Business Media LLC
Date: 03-2011
DOI: 10.1007/BF03326215
Publisher: Inderscience Publishers
Date: 2008
Publisher: Springer Science and Business Media LLC
Date: 27-07-2022
Publisher: Elsevier BV
Date: 05-2016
Publisher: IEEE
Date: 09-2019
Publisher: IEEE
Date: 07-2009
Publisher: Elsevier BV
Date: 09-2013
Publisher: Elsevier BV
Date: 06-2022
Publisher: Springer Science and Business Media LLC
Date: 19-07-2019
Publisher: Elsevier BV
Date: 05-2011
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer International Publishing
Date: 2020
Publisher: Informa UK Limited
Date: 17-04-2023
Publisher: Springer Science and Business Media LLC
Date: 15-07-2013
Publisher: World Scientific Pub Co Pte Lt
Date: 19-11-2019
DOI: 10.1142/S0219686719500355
Abstract: This paper addresses a multi-echelon capacitated location–allocation–inventory problem under uncertainty by providing a robust mixed integer linear programming (MILP) model considering production plants at level one, central warehouses at level two, and the retailers at level three in order to design an optimal supply chain network. In this model, the retailer’s demand parameter is uncertain and just its upper and lower bounds within an interval are known. In order to deal with this uncertainty, a robust optimization approach is used. Then, a self-learning particle swarm optimization (SLPSO) algorithm is developed to solve the problem. The results show that the proposed algorithm outperforms the exact method by providing high quality solutions in the reasonable amount of computational runtime.
Publisher: IEEE
Date: 10-2017
Publisher: Springer Science and Business Media LLC
Date: 29-10-2021
Publisher: Elsevier BV
Date: 12-2017
Publisher: IEEE
Date: 2016
Publisher: Elsevier BV
Date: 10-2006
Publisher: Springer Science and Business Media LLC
Date: 13-07-2017
Publisher: Elsevier BV
Date: 12-2011
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 09-2019
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 07-2019
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 08-2014
Publisher: Springer Science and Business Media LLC
Date: 10-05-2012
Publisher: Springer Science and Business Media LLC
Date: 07-03-2022
Publisher: Elsevier BV
Date: 05-2021
Publisher: Vilnius Gediminas Technical University
Date: 04-10-2012
DOI: 10.3846/16111699.2011.643445
Abstract: A traveling salesman problem (TSP) is an NP-hard optimization problem. So it is necessary to use intelligent and heuristic methods to solve such a hard problem in a less computational time. This paper proposes a novel hybrid approach, which is a data mining (DM) based on multi-objective particle swarm optimization (MOPSO), called intelligent MOPSO (IMOPSO). The first step of the proposed IMOPSO is to find efficient solutions by applying the MOPSO approach. Then, the GRI (Generalized Rule Induction) algorithm, which is a powerful association rule mining, is used for extracting rules from efficient solutions of the MOPSO approach. Afterwards, the extracted rules are applied to improve solutions of the MOPSO for large-sized problems. Our proposed approach (IMOPSP) conforms to a standard data mining framework is called CRISP-DM and is performed on five standard problems with bi-objectives. The associated results of this approach are compared with the results obtained by the MOPSO approach. The results show the superiority of the proposed IMOPSO to obtain more and better solutions in comparison to the MOPSO approach.
Publisher: Elsevier BV
Date: 08-2014
Publisher: Elsevier BV
Date: 05-2012
Publisher: Springer Science and Business Media LLC
Date: 2017
Publisher: Elsevier BV
Date: 10-2006
Publisher: Springer Science and Business Media LLC
Date: 24-06-2022
DOI: 10.1007/S11356-022-21302-X
Abstract: This study examines two pharmaceutical supply chains (PSCs) under the product life cycle and marketing strategies for the first time. Nash equilibrium between PSCs is based on marketing mix factors (i.e., price, the value provided by the value chain, availability, and promotion) at different periods of product life (i.e., introduction, growth, and maturity). Considering the previous step's outputs, environmental protection, and sustainable development, this study provides a multi-objective mixed-integer nonlinear programming model (MOMINLP) for the design of PSCs to minimize environmental pollution and maximize profit, consumer health level, and brand equity. At this stage of the network design, disruption issues in the manufacturer, distributor, and retailer are considered. Based on the value from the value chain in different periods of product life, different scenarios are considered. Optimizing the supply chain network design (SCND) under uncertainty through the reliability and Six Sigma concepts is examined. The proposed approach is validated with a real-case study in Iran. The results show that the brand equity, pollution created, and supply chain profits decrease with increasing optimization levels. However, the level of consumer health rises with increasing levels of optimization. Based on the obtained results, the total profit of the two supply chains at the optimization level 3σ is 3.6% more than the profit at the optimization level 6σ. The total environmental pollution of the two supply chains at the optimization level 3σ is 1.9% less than the environmental pollution at the optimization level 1.285σ. The total consumer health level of the two supply chains at the optimization level 3σ is 3.3% more than the consumer health level at the optimization level 1.285σ. The total brand equity of the two supply chains at the optimization level 3σ is 2.5% more than the brand equity at the optimization level 6σ. It seems that the optimization level 3σ for the two pharmaceutical supply chains is more appropriate than the other optimization levels.
Publisher: Springer Science and Business Media LLC
Date: 27-04-2014
Publisher: IEEE
Date: 12-2018
Publisher: Elsevier BV
Date: 11-2012
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 02-2021
Publisher: Springer Science and Business Media LLC
Date: 12-2013
Publisher: Elsevier BV
Date: 02-2009
Publisher: Elsevier BV
Date: 06-2017
Publisher: Springer Science and Business Media LLC
Date: 15-12-2018
Publisher: Elsevier BV
Date: 09-2011
Publisher: Elsevier BV
Date: 05-2006
Publisher: SAGE Publications
Date: 07-07-2020
Abstract: Applying artificial intelligence techniques for diagnosing diseases in hospitals often provides advanced medical services to patients such as the diagnosis of leukemia. On the other hand, surgery and bone marrow s ling, especially in the diagnosis of childhood leukemia, are even more complex and difficult, resulting in increased human error and procedure time decreased patient satisfaction and increased costs. This study investigates the use of neuro-fuzzy and group method of data handling, for the diagnosis of acute leukemia in children based on the complete blood count test. Furthermore, a principal component analysis is applied to increase the accuracy of the diagnosis. The results show that distinguishing between patient and non-patient in iduals can easily be done with adaptive neuro-fuzzy inference system, whereas for classifying between the types of diseases themselves, more pre-processing operations such as reduction of features may be needed. The proposed approach may help to distinguish between two types of leukemia including acute lymphoblastic leukemia and acute myeloid leukemia. Based on the sensitivity of the diagnosis, experts can use the proposed algorithm to help identify the disease earlier and lessen the cost.
Publisher: Springer International Publishing
Date: 2021
Publisher: Informa UK Limited
Date: 12-05-2022
Publisher: Elsevier BV
Date: 02-2022
DOI: 10.1016/J.COMPBIOMED.2021.105148
Abstract: Operating rooms are among the most high-risk and vital parts of a hospital. Therefore, one of the most fundamental tasks of risk management is maintaining the safety of operating rooms. Resilience engineering (RE) can be introduced as a model for overcoming problems, and it seeks ways to raise success rates by focusing on and addressing complexities. To this end, an RE-based framework is presented to evaluate the performance of operating rooms. First, the RE indicators are identified, and the relative importance of each is calculated via the best-worst method (BWM). Subsequently, the required data are collected from operating room experts using a standard questionnaire. Next, a data envelopment analysis (DEA) method is employed to evaluate the performance of operating rooms in the study case. Lastly, drawing upon the sensitivity analysis and statistical tests, the effect of each RE indicator is examined on the surgical department. Accordingly, some improvement approaches are proposed. Besides, SWOT (strengths, weaknesses, opportunities, and threats) analysis is used to extract appropriate strategies to improve performance. To the best of our knowledge, this paper is the first to evaluate the performance of operating rooms quantitatively in terms of RE indicators, and the framework presented in this paper can have practical applications in different operating rooms.
Publisher: Elsevier BV
Date: 05-2016
Publisher: Springer Science and Business Media LLC
Date: 08-04-2023
Publisher: Elsevier BV
Date: 11-2005
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 10-2006
Publisher: Springer Science and Business Media LLC
Date: 18-07-2019
Publisher: Springer Science and Business Media LLC
Date: 04-10-2012
Publisher: SciTech Solutions
Date: 03-09-2018
Publisher: Springer Science and Business Media LLC
Date: 04-10-2012
Publisher: Springer Science and Business Media LLC
Date: 04-10-2012
Abstract: This paper considers a three-stage assembly flowshop scheduling problem with sequence-dependent setup times at the first stage and blocking times between each stage in such a way that the weighted mean completion time and makespan are minimized. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time using traditional approaches or optimization tools is extremely difficult. Thus, this paper proposes a meta-heuristic method based on simulated annealing (SA) in order to solve the given problem. Finally, the computational results are shown and compared in order to show the efficiency of our proposed SA.
Publisher: Elsevier BV
Date: 03-2013
Publisher: Informa UK Limited
Date: 17-03-2023
Publisher: Springer Science and Business Media LLC
Date: 26-06-2023
DOI: 10.1038/S41591-023-02408-2
Abstract: While over 100 genes have been associated with autism, little is known about the prevalence of variants affecting them in in iduals without a diagnosis of autism. Nor do we fully appreciate the phenotypic ersity beyond the formal autism diagnosis. Based on data from more than 13,000 in iduals with autism and 210,000 undiagnosed in iduals, we estimated the odds ratios for autism associated to rare loss-of-function (LoF) variants in 185 genes associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the correlates of these variants in in iduals without a diagnosis of autism. We show that these variants are associated with a small but significant decrease in fluid intelligence, qualification level and income and an increase in metrics related to material deprivation. These effects were larger for autism-associated genes than in other LoF-intolerant genes. Using brain imaging data from 21,040 in iduals from the UK Biobank, we could not detect significant differences in the overall brain anatomy between LoF carriers and non-carriers. Our results highlight the importance of studying the effect of the genetic variants beyond categorical diagnosis and the need for more research to understand the association between these variants and sociodemographic factors, to best support in iduals carrying these variants.
Publisher: Elsevier BV
Date: 09-2011
Publisher: Growing Science
Date: 07-2012
Publisher: Elsevier BV
Date: 04-2012
Publisher: Informa UK Limited
Date: 10-2013
Publisher: Emerald
Date: 30-08-2023
Abstract: Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies. By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model. Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis. A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability. The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies.
Publisher: Springer Science and Business Media LLC
Date: 25-04-2013
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 09-2012
Publisher: Springer Singapore
Date: 2020
Publisher: Informa UK Limited
Date: 16-10-2020
Publisher: Wiley
Date: 14-07-2023
DOI: 10.1111/WEJ.12892
Abstract: The problem of water scarcity and water crisis (e.g., stable water resources, reduced rainfall, increased urban population growth and lack of proper management of water consumption in urban and domestic water) has recently become a significant issue. Therefore, examining the behaviour of Tehran Province Water and Wastewater (TPWW) subscribers to identify high‐consumption subscribers and explain methods to encourage and educate them more about the correct water consumption pattern can help deal with this crisis. This study aims to use machine learning algorithms to build a robust model for the classification of subscribers in Tehran. Then, new subscribers can be classified into similar classes. For this reason, ensemble algorithms, support vector machines and neural networks are used to predict subscribers' behaviour. Then, the random forest algorithm from the set of ensemble algorithms is considered the best model for the TPWW case with 99% and 98% in train and test accuracy, respectively.
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2019
DOI: 10.3934/NACO.2019014
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 06-04-2023
Publisher: Elsevier BV
Date: 02-2013
Publisher: Elsevier BV
Date: 07-2015
Publisher: IEEE
Date: 12-2013
Publisher: Growing Science
Date: 2012
Publisher: Elsevier BV
Date: 02-2014
Publisher: Informa UK Limited
Date: 26-02-2020
Publisher: Informa UK Limited
Date: 04-2008
Publisher: Springer Science and Business Media LLC
Date: 17-09-2010
Publisher: Elsevier BV
Date: 03-2011
Publisher: Springer Science and Business Media LLC
Date: 09-2019
Publisher: Informa UK Limited
Date: 02-2015
Publisher: Elsevier BV
Date: 2010
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 10-2012
Publisher: IEEE
Date: 12-2019
Publisher: Informa UK Limited
Date: 24-08-2016
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 02-2018
Publisher: Elsevier BV
Date: 02-2013
Publisher: Springer International Publishing
Date: 2021
Publisher: Elsevier BV
Date: 09-2010
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 04-2014
Publisher: Elsevier BV
Date: 03-2006
Publisher: Informa UK Limited
Date: 15-10-2013
Publisher: Elsevier BV
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 18-11-2015
Publisher: Springer International Publishing
Date: 2015
Publisher: Springer Science and Business Media LLC
Date: 27-09-2014
Publisher: Springer International Publishing
Date: 2015
Publisher: Informa UK Limited
Date: 09-11-2021
Publisher: Inderscience Publishers
Date: 2014
Publisher: Elsevier BV
Date: 03-2010
Publisher: Springer Science and Business Media LLC
Date: 11-08-2011
Publisher: Inderscience Publishers
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 08-11-2019
DOI: 10.1007/S10479-019-03430-9
Abstract: This paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.
Publisher: Inderscience Publishers
Date: 2005
Publisher: Engineering, Technology & Applied Science Research
Date: 16-02-2019
DOI: 10.48084/ETASR.2474
Abstract: The transition to alternative fuels is obligatory due to the finite amount of available fossil fuels and their rising prices. However, the transition cannot be done unless enough infrastructure exists. A very important infrastructure is the fueling station. As establishing alternative-fuel stations is expensive, the problem of finding the optimal number and locations of initial alternative-fuel stations emerges and it is investigated in this paper. A mixed-integer linear programming (MILP) formulation is proposed to minimize the costs using net present value (NPV) technique. The proposed formulation considers the criteria of the two most common models in the literature for such a problem, namely P-median model and flow refueling location model (FRLM). A decision support system is developed for the users to be able to control the parameter values and run different scenarios. For case study purposes, the method is used to find the optimal number and locations of the alternative-fuel stations in the city of Chicago. Some data wrangling techniques are used to overcome the inability of the method to solve very large-scale problems.
Publisher: Springer Science and Business Media LLC
Date: 10-03-2018
Publisher: Informa UK Limited
Date: 06-2009
Publisher: Elsevier BV
Date: 12-1998
Publisher: Informa UK Limited
Date: 2014
Publisher: Elsevier BV
Date: 10-2019
Publisher: SciTech Solutions
Date: 04-09-2017
Publisher: American Society of Civil Engineers (ASCE)
Date: 10-2013
Publisher: Emerald
Date: 17-06-2021
Abstract: To avoid sub-optimization in wheat storage centers, one of the most strategic facilities, it is necessary to review and relocate them to be optimized regularly. The present study aims to propose an integrated method using geographic information systems (GISs) and an appropriate weighting algorithm for the relocation of wheat storage facilities. To achieve the goal mentioned above, sustainability pillars in facility location and relocation are initially developed afterward, a set of suitable criteria are obtained from various scientific resources. Then, the weight of each sustainable development pillar and its corresponding sub-criteria were identified through utilizing the best–worst method (BWM). By applying the obtained weights in the ArcGIS software package, various geographical layers were designed, and land-use planning, logistics planning and sustainable logistics planning are carried out in the regions. The regions are ranked based on the scores obtained in the processes, and the best regions are selected for sustainable relocation problem. A case study including 430 regions (counties) in Iran is conducted to evaluate the efficiency of the suggested approach. The study results indicate that Iran possesses a superior state for establishing wheat storage centers in terms of infrastructural and social aspects. Also, it is established that 16% of counties are recognized as sustainable locations for relocating the wheat storage facilities. There is no most suitable analysis of the wheat storage facilities, as well as their strategic position in the supply chain, and there is a lack of considering sustainability in wheat storage facility location, despite the particular importance of it to the supply chain. This framework is applied in an Iranian wheat-bread supply chain to find the best sustainable facilities. It is noted that this algorithm can be applied in other strategic facilities by minor and some major changes. Decision-makers can apply the proposed methodology to find the best relocation sites for wheat storage facilities as the main part of wheat-bread supply chain in order to prevent sub-optimization and improve the efficiency of their supply chain.
Publisher: IEEE
Date: 12-2008
Publisher: IEEE
Date: 09-2011
Publisher: Springer Science and Business Media LLC
Date: 10-01-2008
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 12-2017
Publisher: Elsevier BV
Date: 08-2009
Publisher: Wiley
Date: 22-07-2019
DOI: 10.1111/COIN.12228
Publisher: Growing Science
Date: 07-2012
Publisher: Elsevier BV
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 18-02-2022
Publisher: Springer Science and Business Media LLC
Date: 10-03-2020
Publisher: Elsevier BV
Date: 03-2017
Publisher: Springer Science and Business Media LLC
Date: 30-10-2013
Publisher: Elsevier BV
Date: 03-2019
Publisher: Inderscience Publishers
Date: 2017
Publisher: Growing Science
Date: 2014
Publisher: Informa UK Limited
Date: 23-07-2015
Publisher: Springer Science and Business Media LLC
Date: 12-08-2023
Publisher: Elsevier BV
Date: 02-2019
Publisher: IEEE
Date: 12-2007
Publisher: Springer International Publishing
Date: 15-06-2020
Publisher: Informa UK Limited
Date: 14-06-2016
Publisher: Wiley
Date: 19-08-2021
DOI: 10.1002/NET.22074
Abstract: Here, a mixed‐integer linear programming model is developed to represent a transportation system of students traveling from/to a university c us. The concept of ridesharing is used and the mechanism of combinatorial auctions is incorporated within a routing‐based model. The mathematical model is based on the vehicle routing problem along with appropriate constraints accommodating features that express the auction clearing phase. A hybrid heuristic‐based optimization framework, that takes advantage of meta‐heuristic algorithms to improve an initial solution, is also developed to solve large‐sized instances of the problem. Three meta‐heuristics, namely particle swarm optimization, dragonfly algorithm, and imperialist competitive algorithm, are implemented in the proposed framework, whose performances are assessed and compared. Moreover, two improvement heuristic procedures that attempt to improve the outcomes of the foregoing meta‐heuristics are proposed and compared as well.
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 2014
Publisher: Informa UK Limited
Date: 08-2012
Publisher: Growing Science
Date: 2011
Publisher: Informa UK Limited
Date: 22-01-2019
Publisher: American Society of Civil Engineers (ASCE)
Date: 06-2018
Publisher: Springer Science and Business Media LLC
Date: 16-05-2018
Publisher: Elsevier BV
Date: 09-2011
Publisher: SciTech Solutions
Date: 10-2017
Publisher: Elsevier BV
Date: 04-2013
Publisher: IEEE
Date: 07-2010
Publisher: Springer Science and Business Media LLC
Date: 13-01-2016
Publisher: Elsevier BV
Date: 11-2009
Publisher: Elsevier BV
Date: 05-2013
Publisher: SciTech Solutions
Date: 10-2017
Publisher: Elsevier BV
Date: 2019
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 10-2018
Publisher: Springer Science and Business Media LLC
Date: 03-02-2012
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 2015
Publisher: SAGE Publications
Date: 16-12-2014
Abstract: This article deals with a redundancy allocation problem in series–parallel systems with a cold standby strategy, in which component time to failure follows an exponential distribution that has constant hazard rate. Ex les of this kind of system are systems composed of electronic components (e.g. transistors, capacitors, resistors and integrated circuits) used in control systems, power generators and the like, which needs to be supported by standby components to prevent unexpected failures. In this article, the reliability of each component is imprecise in terms of interval data, and only the lower and upper bounds of reliabilities are known. The problem is formulated through Min-Max regret criterion, which is commonly used to define robust solutions. The resulted problem formulation contains unlimited numbers of constraints, and Benders’ decomposition method is implemented to deal with the given problem. This method is compared with an enumeration method and a stochastic search method called genetic algorithm to show its effectiveness. The results show that the proposed Benders’ decomposition method is conducive to the same results in a reasonable amount of time. The performance of the proposed model using Benders’ decomposition method is also examined over different problem sizes, and the associated results are analyzed. The results show that for large-sized problems, Benders’ decomposition method is converged with fewer numbers of cuts, and therefore, it is time-economic for solving such problems.
Publisher: Elsevier BV
Date: 12-2017
Publisher: Elsevier BV
Date: 12-2021
Publisher: Emerald
Date: 13-04-2021
DOI: 10.1108/ECAM-08-2020-0617
Abstract: The construction industry is a key driver of economic growth. However, the adverse impacts of construction and demolition waste (CDW) resulted from the active construction projects on the economy, environment, public health and social life necessitates an appropriate control and management of this waste stream. Developing and promoting the construction and demolition waste management (CDWM) hierarchy program at the strategic level is essential. This study aims to propose a hybrid decision model that hybridizes the Integrated Determination of Objective Criteria Weights (IDOCRIW) and weighted aggregated sum product assessment (WASPAS) under a fuzzy environment. The proposed method ranks the potential strategic alternatives by the sustainable development criteria to improve the performance of CDWM. As indicated in the results, the fuzzy approach in the decision-making process enables the transformation of linguistic variables into fuzzy numbers that show uncertainty and ambiguity in real-world systems. Moreover, the close correlation between the final ranking of the proposed methodology and the average priority order of the strategic alternatives obtained by five different multi-criteria decision-making (MCDM) methods implies the validity of the model performance. This proposed model is an appropriate tool to effectively decide on the development of CDWM from a strategic point of view. It aims to establish an MCDM framework for the evaluation of effective strategies for CDWM according to the indices of sustainable development. Implementing proper operational plans and conducting research in CDWM has the highest priority, and enacting new and more stringent laws, rules and regulations against the production of CDW has secondary priority. This study contributes to the field by optimizing the CDWM by applying the top-priority strategies resulted from the proposed fuzzy hybrid MCDM methodology by the decision-makers or policy-makers to reach the best managerial strategic plan. In the proposed methodology, the IDOCRIW technique is utilized and updated with the triangular fuzzy numbers for the first time in the literature to derive the weights of sustainable development criteria. The fuzzy WASPAS method is utilized for evaluation and providing a final ranking of the strategic alternatives.
Publisher: Omnia Publisher SL
Date: 15-05-2017
DOI: 10.3926/JIEM.2170
Abstract: Purpose: Nowadays, governments and people pay more attention to use green products due to environmental pollution, irreplaceable energy and shortage of resources. Green products are resulted from the application of green supply chain management strategies to the organizations' performance strategies, so that we can reduce environmental pollutants and wastes and take a step towards saving energy with limited resources.Methodology: In this paper, the effect of reducing energy consumption in green supply chain is examined by using queuing theory and transportation models. Data was generated and solved by a commercial optimization epackage.Findings: The findings indicate that suitable assignment of existing transportation fleet with specified capacity, and using queueing theory in a closed-loop network to reduce the queue length and handle congestion, can cause a reduction in energy consumption by optimizing transportation and waiting times in a green supply chain.Originality/value: Adopting investment strategy in improving the environmental performance of the supply chain, will yield in many advantages and benefits. This article investigates the effect of queuing theory on reducing waiting time, optimizing energy consumption in green supply chain, and consequently decreasing pollution.
Publisher: Elsevier BV
Date: 09-2011
Publisher: Springer Science and Business Media LLC
Date: 12-05-2020
Publisher: Elsevier BV
Date: 10-2012
Publisher: IEEE
Date: 07-2014
Publisher: Springer Science and Business Media LLC
Date: 24-05-2014
Publisher: Springer Science and Business Media LLC
Date: 21-09-2011
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 11-2007
Publisher: Informa UK Limited
Date: 29-06-2023
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 02-2013
Publisher: Springer Science and Business Media LLC
Date: 05-07-2022
Publisher: Springer Science and Business Media LLC
Date: 07-01-2011
Publisher: Elsevier BV
Date: 11-2005
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 02-2019
Publisher: IEEE
Date: 03-2014
Publisher: Elsevier BV
Date: 07-2011
Publisher: Springer International Publishing
Date: 11-07-2021
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 06-2019
Publisher: IEEE
Date: 12-2007
Publisher: Elsevier BV
Date: 06-2020
Publisher: Growing Science
Date: 04-2012
Publisher: SAGE Publications
Date: 04-10-2018
Abstract: A train makeup problem specifies the frequency of freight trains and allocates the shipment to trains based on the desired shipment-to-train allocation scheme. In this study, a multi-objective model is presented for train makeup, taking into account the locomotive limitations on a railway network. The objective functions include maximization of the total profit and the customers' satisfaction level as well as minimization of the total number of shunting operations in yards, the unused capacity of trains, the total lost demand, the transfer time of trains and the total fuel consumed. The main constraints of the model are the establishment of flow balance for each yard and each demand, the upper and lower limits of the train length, and the upper limit of the following: train makeup in each yard, shunting operations in each yard, capacity of each train and locomotive utilization in each period. Goal programming and L p metric methods are used for the multi-objective problem considered. For solving this problem, a hybrid firefly algorithm is also proposed. A number of test problems based on the simulation are generated and solved by using the proposed algorithm. Furthermore, a real-time case study based on the Iranian Railway Network is used. The results show the potential of the presented model and the efficiency of the hybrid algorithm, which can be used for real-time railway problems.
Publisher: Growing Science
Date: 04-2012
Publisher: Springer Science and Business Media LLC
Date: 14-10-2015
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 12-2022
Publisher: Informa UK Limited
Date: 13-12-2014
Publisher: IEEE
Date: 12-2011
Publisher: Elsevier BV
Date: 2023
Publisher: IEEE
Date: 12-2019
Publisher: Elsevier BV
Date: 06-2012
Publisher: Elsevier BV
Date: 10-2018
Publisher: Informa UK Limited
Date: 2011
Publisher: Growing Science
Date: 2011
Publisher: Elsevier BV
Date: 08-2007
Publisher: Mechanical Engineering Faculty in Slavonski Brod
Date: 14-06-2020
Publisher: Elsevier BV
Date: 2012
Publisher: Elsevier BV
Date: 06-2016
Publisher: Springer Science and Business Media LLC
Date: 19-07-2013
Publisher: Elsevier BV
Date: 05-2013
Publisher: IEEE
Date: 12-2007
Publisher: Informa UK Limited
Date: 11-2020
Publisher: Informa UK Limited
Date: 29-01-2018
Publisher: Springer Science and Business Media LLC
Date: 06-03-2017
Publisher: Elsevier BV
Date: 2019
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 10-2014
Publisher: SciTech Solutions
Date: 03-06-2019
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 05-2019
Publisher: Elsevier BV
Date: 08-2019
Publisher: Vilnius Gediminas Technical University
Date: 20-08-2018
DOI: 10.3846/TRANSPORT.2018.1558
Abstract: In this paper, an Integer Linear Programming (ILP) has been developed for rebalancing the stations of a Periodic Bike Relocation Problem (PBRP) in multiple periods. The objective function of the mathematical model is reducing costs of implementing trucks, transportation between stations and holding bikes on trucks during rebalancing. The variables we are following them in this model are conducting the optimal route in several periods, using the most appropriate trucks for these routes, and determining the best program for loading/unloading bikes for stations. The distinguishing features of the proposed model are considering several bike types, several exclusive trucks and several time periods. Finally, a numerical ex le confirms the applicability of the proposed model.
Publisher: Elsevier BV
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2013
Publisher: MDPI AG
Date: 25-12-2021
DOI: 10.3390/SU14010202
Abstract: Brick making contributes significantly to the of supply materials for the building industry. The majority of brick production sectors, especially in developing countries, employ polluting and energy-inefficient technologies. Due to the increasing pressures on manufacturing firms to improve economic performance and growing environmental protection issues, sustainable and clean production is the main concern for brick makers. This paper considers the technological, economic, environmental, social, and energy-oriented criteria to select the optimal brick production technologies. Therefore, technology selection is viewed as a multi-criteria group decision-making (MCGDM) problem. This research proposes a novel hybrid fuzzy MCGDM (HFMCGDM) model to tackle the problem. In this respect, first of all, the modified triangular fuzzy pair-wise comparison (MTFPC) method is proposed to compute the local weights of criteria and sub-criteria. Then, a fuzzy DEMATEL (FDEMATEL) method is presented to calculate the interdependencies between and within the criteria. Moreover, the integration of MTFPC and FDEMATEL methods is applied to calculate the global criteria weights. Afterward, a novel method is proposed to determine the experts’ weight. Considering the last aggregation approach to diminish data loss, a new version of a fuzzy TOPSIS method is proposed to find the local and global priorities of the candidates. Then, a case study is given to demonstrate the applicability and superiority of the proposed methodology. To get a deeper view about considering kilns, energy and environmental performance of which has been investigated. Moreover, a comparative analysis is presented to illuminate the merits of the proposed methodology. Eventually, a sensitivity analysis is conducted to peruse the influence of criteria weights on ranking order.
Publisher: Elsevier BV
Date: 03-2016
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 10-2019
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Elsevier BV
Date: 04-2012
Publisher: Elsevier BV
Date: 05-2009
Publisher: Elsevier BV
Date: 02-2019
Publisher: Springer Science and Business Media LLC
Date: 17-08-2023
Publisher: Elsevier BV
Date: 08-2021
Publisher: Informa UK Limited
Date: 07-01-2015
Publisher: Elsevier BV
Date: 2007
Publisher: BMJ
Date: 09-2021
DOI: 10.1136/BMJOPEN-2020-045628
Abstract: Gender identity development services (GIDS) worldwide have seen a significant increase in referrals in recent years. Many of these referrals consist of children and young people (CYP) who experience gender-related distress. This study aims to improve understanding of outcomes of CYP referred to the UK GIDS, specifically regarding gender identity, mental health, physical health and quality of life. The impact of factors such as co-occurring autism and early social transition on outcomes over time will be explored. This is a prospective cohort study of CYP aged 3–14 years when referred to the UK GIDS. Eligible participants will be ≤14 years at the time their referral was accepted and will be on the waitlist for the service when baseline measures are completed. Children aged under 12 years will complete the measures in an interview format with a researcher, while young people aged 12 years and over and their parents/caregivers will complete online or paper-based questionnaires. Participants will complete follow-up measures 12 months and 24 months later. The final s le size is expected to be approximately 500. Logistic regression models will be used to explore associations between prespecified explanatory variables and gender dysphoria. Appropriate regression models will also be used to investigate explanatory variables for other outcomes. Subgroup analyses based on birth-assigned gender, age at referral and co-occurring autistic traits will be explored. The study has been approved by the Health Research Authority and London – H stead Research Ethics Committee (reference: 19/LO/0857). The study findings will be published in peer-reviewed journals and presented at both conferences and stakeholder events. Findings will be used to inform clinical practice.
Publisher: Tsinghua University Press
Date: 02-04-2020
Publisher: Informa UK Limited
Date: 18-05-2016
Publisher: SciTech Solutions
Date: 05-2018
Publisher: Tsinghua University Press
Date: 03-04-2022
Publisher: Oxford University Press (OUP)
Date: 06-2022
DOI: 10.1093/JCDE/QWAC042
Abstract: Construction material delivery to post-disaster reconstruction projects is challenging because of the resource and time limitations that follow a large-scale disaster. There is compelling evidence that inadequate planning jeopardises the success of a large number of post-disaster reconstruction projects. Thus, the current study proposes an integrated approach to facilitate the procurement planning of construction materials following a large-scale disaster. The proposed approach clustered the location of construction projects using a differential evolution (DE)-K-prototypes, a new partitional clustering algorithm based on DE and K-prototypes, method. Then, using a permanent matrix prioritises cluster points based on route reliability-affecting factors. The model’s objectives are to minimise the total travel time, maximise the reliability of the route, and minimise the total weighted undelivered materials to projects. In the case of distribution of material through land vehicles, the possibility of breakdowns in the vehicle is considered, allowing for the determination of vehicle breakdown under various scenarios and the minimisation of undelivered materials to projects. As a result of the uncertain character of the disaster, the demands of construction projects are fuzzy, and Jimenez’s method is used to handle it. Due to the complexity of the problem, two algorithms are proposed, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and a non-dominated sorting genetic algorithm-II (NSGA-II). The results confirm that the proposed MOEA/D has a higher accuracy while NSGA-II has a shorter computational time. By providing new theoretical perspectives on disaster recovery strategies in the construction sector, this study contributes to the growing body of knowledge about disaster recovery strategies in the sector. The findings of this study can be employed to develop an integrated planning system for the delivery of construction materials to post-disaster reconstruction projects in disaster-prone countries.
Publisher: Elsevier BV
Date: 11-2020
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 04-2014
Publisher: Elsevier BV
Date: 2009
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 04-2014
Publisher: Springer Science and Business Media LLC
Date: 14-06-2007
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 2011
Publisher: Elsevier BV
Date: 08-2011
Publisher: Springer Science and Business Media LLC
Date: 17-10-2013
Publisher: Springer Science and Business Media LLC
Date: 04-12-2021
Publisher: Elsevier BV
Date: 07-2018
Publisher: IEEE
Date: 2019
Publisher: Elsevier BV
Date: 04-2017
Publisher: Informa UK Limited
Date: 30-03-2021
Publisher: Informa UK Limited
Date: 30-03-2017
Publisher: Springer Science and Business Media LLC
Date: 04-05-2014
Publisher: Elsevier BV
Date: 12-2009
Publisher: BMJ
Date: 11-2021
DOI: 10.1136/BMJOPEN-2021-054895
Abstract: Specialist gender services for children and young people (CYP) worldwide have experienced a significant increase in referrals in recent years. As rates of referrals increase, it is important to understand the characteristics and profile of CYP attending these services in order to inform treatment pathways and to ensure optimal outcomes. A retrospective observational study of clinical health records from specialist gender services for CYP in the UK and the Netherlands. The retrospective analysis will examine routinely collected clinical and outcome measures data including demographic, clinical, gender identity-related and healthcare resource use information. Data will be reported for each service and also compared between services. This study forms part of a wider programme of research investigating outcomes of gender identity in children (the Longitudinal Outcomes of Gender Identity in Children study). The proposed study has been approved by the Health Research Authority and London—H stead Research Ethics Committee as application 19/LO/0181. The study findings will be published in peer-reviewed journals and presented at both conferences and stakeholder events.
Publisher: Elsevier BV
Date: 03-2013
Publisher: Springer Science and Business Media LLC
Date: 22-04-2021
Publisher: Springer Science and Business Media LLC
Date: 06-04-2022
DOI: 10.1038/S41586-022-04554-Y
Abstract: Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify in idual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future s le of MRI data ( www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the ersity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of in iduals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of in idual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
Publisher: Springer Science and Business Media LLC
Date: 11-11-2015
Publisher: Elsevier BV
Date: 03-2013
Publisher: IEEE
Date: 12-2019
Publisher: IEEE
Date: 11-2010
Publisher: Informa UK Limited
Date: 04-2008
Publisher: Springer Science and Business Media LLC
Date: 09-11-2014
Publisher: Hindawi Limited
Date: 2015
DOI: 10.1155/2015/914108
Abstract: Performance assessment during the time and along with strategies is the most important requirements of top managers. To assess the performance, a balanced score card (BSC) along with strategic goals and a data envelopment analysis (DEA) are used as powerful qualitative and quantitative tools, respectively. By integrating these two models, their strengths are used and their weaknesses are removed. In this paper, an integrated framework of the BSC and DEA models is proposed for measuring the efficiency during the time and along with strategies based on the time delay of the lag key performance indicators (KPIs) of the BSC model. The causal relationships during the time among perspectives of the BSC model are drawn as dynamic BSC at first. Then, after identifying the network-DEA structure, a new objective function for measuring the efficiency of nine subsidiary refineries of the National Iranian Oil Refining and Distribution Company (NIORDC) during the time and along with strategies is developed.
Publisher: Informa UK Limited
Date: 04-2011
Publisher: Informa UK Limited
Date: 16-12-2014
Publisher: Informa UK Limited
Date: 25-04-2018
Publisher: Elsevier BV
Date: 2019
Publisher: IEEE
Date: 04-2007
Publisher: Springer Science and Business Media LLC
Date: 07-10-2022
Publisher: Informa UK Limited
Date: 2012
Publisher: Elsevier BV
Date: 2019
Publisher: IEEE
Date: 12-2007
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Inderscience Publishers
Date: 2015
Publisher: Springer Singapore
Date: 24-08-2017
Publisher: Elsevier BV
Date: 12-2013
Publisher: Informa UK Limited
Date: 18-02-2016
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 02-2009
Publisher: Springer Science and Business Media LLC
Date: 18-06-2013
Publisher: Growing Science
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 20-04-2020
Publisher: Springer Science and Business Media LLC
Date: 28-10-2022
Publisher: Informa UK Limited
Date: 28-08-2020
Publisher: Elsevier BV
Date: 12-2011
Publisher: SAGE Publications
Date: 18-03-2009
Abstract: This paper presents a novel, multi-objective mixed-integer programming model for designing a cellular manufacturing system (CMS) that minimizes the total cost and maximizes the overall system reliability. In general, it is impossible to avoid production interruptions while handling machine breakdowns. In this situation, changing the process route dynamically can provide a quick response to meet production requirements. By assuming alternative process plans for operation—part requirements, the concept of the ‘reliable route’ proposed in the literature is extended. In a redundant reliability system with a series—parallel configuration, each reliable route is associated with an operation of a part (i.e. an operation—part) as a parallel subsystem. This route consists of a number of units or alternative machines allocated to cells in such a way that parts are processed with the maximum reliability for a given period of time. When an alternative machine breaks down, unprocessed parts are transferred to the next predetermined machine on the reliable route in order to complete their processes. While the reliable route approach increases the overall system reliability, the operational costs of the system also increase. To assess the present proposed model as a useful decision tool for the manager, various numerical ex les are solved and analysed. Finally, the related computational results are reported.
Publisher: Informa UK Limited
Date: 14-09-2016
Publisher: International Digital Organization for Scientific Information (IDOSI)
Date: 2011
Publisher: Informa UK Limited
Date: 30-05-2016
Publisher: Springer Science and Business Media LLC
Date: 14-04-2011
Publisher: Elsevier BV
Date: 08-2023
Publisher: Inderscience Publishers
Date: 2016
Publisher: IEEE
Date: 2019
Publisher: Growing Science
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 20-05-2022
Publisher: Elsevier BV
Date: 12-2015
Publisher: Production Engineering Institute (PEI), Faculty of Mechanical Engineering
Date: 12-03-2018
Publisher: Elsevier BV
Date: 09-2016
Location: Iran (Islamic Republic of)
No related grants have been discovered for Kurnia Wijayanti.