A Multi-Objective Optimization Approach Based on an Enhanced Particle Swarm Optimization Algorithm With Evolutionary Game Theory

Due to conflicts among objectives of multi-objective optimization (MO) problems, it remains challenging to gain high-quality Pareto fronts for different MO issues. Attempt to handle this challenge and obtain high-performance Pareto fronts, this paper proposes a novel MO optimizer via leveraging part...

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Vydané v:	IEEE access Ročník 11; s. 77566 - 77584
Hlavní autori:	Yin, Kaiyang, Tang, Biwei, Li, Ming, Zhao, Huanli
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Archives & records Benchmark testing Benchmarks Convergence convergence investigation Evolutionary algorithms Evolutionary computation evolutionary game theory Game theory Mathematical analysis Multi-objective optimization Multiple objective analysis Optimization Parameter modification Parametric analysis Pareto analysis pareto front Pareto optimization Particle swarm optimization Sorting
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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