Decomposition-Based Multiobjective Optimization Algorithms With Adaptively Adjusting Weight Vectors and Neighborhoods

The decomposition-based multiobjective optimization algorithm (MOEA/D) is an effective method of solving a multiobjective optimization problem (MOP). The main idea of MOEA/D is that the objectives are weighted through different vectors to form different subproblems, and an optimal solution set is ob...

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Vydáno v:	IEEE transactions on evolutionary computation Ročník 27; číslo 5; s. 1485 - 1497
Hlavní autoři:	Zhao, Qian, Guo, Yinan, Yao, Xiangjuan, Gong, Dunwei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptive mechanism Algorithms Convergence Decomposition decomposition-based multiobjective optimization algorithm (MOEA/D) Evolutionary algorithms Linear programming Multiple objective analysis neighborhood adjustment Neighborhoods Optimization Pareto optimization Population density Runtime Search problems Sociology Statistics Vectors (mathematics) weight vector
ISSN:	1089-778X, 1941-0026
On-line přístup:	Získat plný text
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