A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables

This paper presents a new multi-objective optimization algorithm called FC-MOPSO for optimal design of engineering problems with a small number of function evaluations. The proposed algorithm expands the main idea of the single-objective particle swarm optimization (PSO) algorithm to deal with const...

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Vydané v:	Structural and multidisciplinary optimization Ročník 57; číslo 2; s. 509 - 533
Hlavní autori:	Mokarram, Vahid, Banan, Mohammad Reza
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2018 Springer Nature B.V
Predmet:	Algorithms Computational Mathematics and Numerical Analysis Continuity (mathematics) Design engineering Design optimization Engineering Engineering Design Mopping Multiple objective analysis Particle swarm optimization Research Paper Theoretical and Applied Mechanics Structural optimization Particle swarm optimization Multi-objective optimization
ISSN:	1615-147X, 1615-1488
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Abstract	This paper presents a new multi-objective optimization algorithm called FC-MOPSO for optimal design of engineering problems with a small number of function evaluations. The proposed algorithm expands the main idea of the single-objective particle swarm optimization (PSO) algorithm to deal with constrained and unconstrained multi-objective problems (MOPs). FC-MOPSO employs an effective procedure in selection of the leader for each particle to ensure both diversity and fast convergence. Fifteen benchmark problems with continuous design variables are used to validate the performance of the proposed algorithm. Finally, a modified version of FC-MOPSO is introduced for handling discrete optimization problems. Its performance is demonstrated by optimizing five space truss structures. It is shown that the FC-MOPSO can effectively find acceptable approximations of Pareto fronts for structural MOPs within very limited number of function evaluations.
AbstractList	This paper presents a new multi-objective optimization algorithm called FC-MOPSO for optimal design of engineering problems with a small number of function evaluations. The proposed algorithm expands the main idea of the single-objective particle swarm optimization (PSO) algorithm to deal with constrained and unconstrained multi-objective problems (MOPs). FC-MOPSO employs an effective procedure in selection of the leader for each particle to ensure both diversity and fast convergence. Fifteen benchmark problems with continuous design variables are used to validate the performance of the proposed algorithm. Finally, a modified version of FC-MOPSO is introduced for handling discrete optimization problems. Its performance is demonstrated by optimizing five space truss structures. It is shown that the FC-MOPSO can effectively find acceptable approximations of Pareto fronts for structural MOPs within very limited number of function evaluations.
Author	Mokarram, Vahid Banan, Mohammad Reza
Author_xml	– sequence: 1 givenname: Vahid surname: Mokarram fullname: Mokarram, Vahid organization: Department of Civil and Environmental Engineering, School of Engineering, Shiraz University – sequence: 2 givenname: Mohammad Reza surname: Banan fullname: Banan, Mohammad Reza email: banan@shirazu.ac.ir organization: Department of Civil and Environmental Engineering, School of Engineering, Shiraz University
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Snippet	This paper presents a new multi-objective optimization algorithm called FC-MOPSO for optimal design of engineering problems with a small number of function...
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SubjectTerms	Algorithms Computational Mathematics and Numerical Analysis Continuity (mathematics) Design engineering Design optimization Engineering Engineering Design Mopping Multiple objective analysis Particle swarm optimization Research Paper Theoretical and Applied Mechanics
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Title	A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables
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