A Framework to Handle Multimodal Multiobjective Optimization in Decomposition-Based Evolutionary Algorithms

Multimodal multiobjective optimization is to locate (almost) equivalent Pareto optimal solutions as many as possible. While decomposition-based evolutionary algorithms have good performance for multiobjective optimization, they are likely to perform poorly for multimodal multiobjective optimization...

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Vydáno v:	IEEE transactions on evolutionary computation Ročník 24; číslo 4; s. 720 - 734
Hlavní autoři:	Tanabe, Ryoji, Ishibuchi, Hisao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.08.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Benchmark testing Decision making Decomposition Decomposition-based evolutionary algorithms Equivalence Evolutionary algorithms Evolutionary computation Genetic algorithms Indexes multimodal multiobjective optimization Multiple objective analysis Optimization Pareto optimization Pareto optimum Performance enhancement reference vector-based evolutionary algorithms Solution space solution space diversity Spatial diversity
ISSN:	1089-778X, 1941-0026
On-line přístup:	Získat plný text
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