Multi-objective hybrid algorithms for layout optimization in multi-robot cellular manufacturing systems

•Hybrid algorithms to optimize layouts for multi-robot assembly systems are proposed.•Layout area, operation time and manipulability are the three criteria used.•DE, ABC, CSS and PSO are hybridized with genetic algorithm to have four hybrids.•It is found that GA-PSO hybrid performs better over other...

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Vydané v:	Knowledge-based systems Ročník 120; s. 87 - 98
Hlavní autori:	Lim, Zhen Yang, Ponnambalam, S.G., Izui, Kazuhiro
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 15.03.2017 Elsevier Science Ltd
Predmet:	Algorithms Assembly Candidates Cellular manufacture Charged particles Classification Control systems Cooperation Design analysis Design engineering Dummy Evolutionary algorithms Function words Genetic algorithms Genetics Hybrid algorithms Hybrid systems Layout Layout design Manufacturing Multi-robot assembly systems Multiple objective analysis Multiple robots Object transportation Objectives Optimization Pareto optimum Particle swarm optimization Robotics Robots Sorting algorithms Object transportation Hybrid algorithms Layout design Multi-robot assembly systems Evolutionary algorithms
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
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