ORCID Profile
0000-0002-8480-940X
Current Organisation
University of Leeds
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2016
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 12-2014
Publisher: Inderscience Publishers
Date: 2016
Publisher: ASMEDC
Date: 2010
Abstract: Multi-Objective Optimization of a benchmark cogeneration problem known as CGAM cogeneration system has been carried out from Exergetic, Economic and Environmental aspects simultaneously. CGAM Problem designs a cogeneration plant which delivers 30 MW of electricity and 14 kg/s of saturated steam at 20 bars. Since multi-objective calculus based optimization of real energy systems involves very complicated process, one of the most suitable techniques which uses a particular class of search algorithms known as Particle Swarm Optimization (MOPSO) is utilized and the advantages of this method is shown. This approach has been applied to find the set of Pareto optimal solutions with respect to the competing objective functions. In this study the MOPSO algorithm uses 100 particles and 200 iterations. In order to facilitate the problem, the environmental objective function has been defined and expressed in cost terms. The thermodynamic modeling has been implemented comprehensively while economic analysis of this system conducted. Consideration of Five decision variables in modeling process made the final optimal solutions more realistic in comparison with previous studies in this field. Finally the result of optimization is introduced with 100 points on Pareto frontier.
Publisher: Springer Science and Business Media LLC
Date: 05-06-2019
Publisher: Springer Science and Business Media LLC
Date: 12-2011
Publisher: Elsevier BV
Date: 09-2015
Publisher: Springer Science and Business Media LLC
Date: 24-10-2018
Publisher: IEEE
Date: 12-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 10-2019
Publisher: Public Library of Science (PLoS)
Date: 23-10-2015
Publisher: Elsevier BV
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 04-08-2016
Publisher: Elsevier BV
Date: 08-2011
Publisher: SAGE Publications
Date: 03-01-2012
Abstract: This article focuses on the efficient multi-objective particle swarm optimization algorithm to solve multidisciplinary design optimization problems. The objective is to extend the formulation of collaborative optimization which has been widely used to solve single-objective optimization problems. To examine the proposed structure, racecar design problem is taken as an ex le of application for three objective functions. In addition, a fuzzy decision maker is applied to select the best solution along the pareto front based on the defined criteria. The results are compared to the traditional optimization, and collaborative optimization formulations that do not use multi-objective particle swarm optimization. It is shown that the integration of multi-objective particle swarm optimization into collaborative optimization provides an efficient framework for design and analysis of hierarchical multidisciplinary design optimization problems.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Meisam Babaie.