An Adaptive Reference Vector-Guided Evolutionary Algorithm Using Growing Neural Gas for Many-Objective Optimization of Irregular Problems

Most reference vector-based decomposition algorithms for solving multiobjective optimization problems may not be well suited for solving problems with irregular Pareto fronts (PFs) because the distribution of predefined reference vectors may not match well with the distribution of the Pareto-optimal...

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Vydáno v:	IEEE transactions on cybernetics Ročník 52; číslo 5; s. 2698 - 2711
Hlavní autoři:	Liu, Qiqi, Jin, Yaochu, Heiderich, Martin, Rodemann, Tobias, Yu, Guo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.05.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptation Algorithms Clustering algorithms Comparative studies Control systems design Convergence Decomposition Evolutionary algorithms Evolutionary computation Evolutionary many-objective optimization growing neural gas (GNG) Hybrid vehicles irregular Pareto front (PF) Multiple objective analysis Optimization Pareto optimization Pareto optimum Problem solving reference vector Search process Sociology Statistics Topology
ISSN:	2168-2267, 2168-2275, 2168-2275
On-line přístup:	Získat plný text
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