ORCID Profile
0000-0003-0061-4902
Current Organisation
University of Queensland
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2016
Publisher: Maad Rayan Publishing Company
Date: 30-12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: Springer Science and Business Media LLC
Date: 04-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2019
Publisher: Springer Science and Business Media LLC
Date: 08-2014
Publisher: Elsevier BV
Date: 12-2017
Publisher: MIT Press - Journals
Date: 03-2017
DOI: 10.1162/EVCO_R_00180
Abstract: This paper reviews recent studies on the Particle Swarm Optimization (PSO) algorithm. The review has been focused on high impact recent articles that have analyzed and/or modified PSO algorithms. This paper also presents some potential areas for future study.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Publisher: Elsevier BV
Date: 10-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Publisher: Hindawi Limited
Date: 2014
DOI: 10.1155/2014/967254
Abstract: This paper presents a hybrid evolutionary algorithm to deal with the wheat blending problem. The unique constraints of this problem make many existing algorithms fail: either they do not generate acceptable results or they are not able to complete optimization within the required time. The proposed algorithm starts with a filtering process that follows predefined rules to reduce the search space. Then the linear-relaxed version of the problem is solved using a standard linear programming algorithm. The result is used in conjunction with a solution generated by a heuristic method to generate an initial solution. After that, a hybrid of an evolutionary algorithm, a heuristic method, and a linear programming solver is used to improve the quality of the solution. A local search based posttuning method is also incorporated into the algorithm. The proposed algorithm has been tested on artificial test cases and also real data from past years. Results show that the algorithm is able to find quality results in all cases and outperforms the existing method in terms of both quality and speed.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
No related grants have been discovered for Mohammadreza Bonyadi.