A dynamic multi-objective particle swarm optimization algorithm based on adversarial decomposition and neighborhood evolution

Many multi-objective optimization problems in the real world are dynamic, with objectives that conflict and change over time. These problems put higher demands on the algorithm’s convergence performance and the ability to respond to environmental changes. Confronting these two points, this paper pro...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 69; S. 100987
Hauptverfasser:	Zheng, Jinhua, Zhang, Zeyu, Zou, Juan, Yang, Shengxiang, Ou, Junwei, Hu, Yaru
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.03.2022
Schlagworte:	Adversarial decomposition Dynamic multi-objective optimization Particle swarm optimization Dynamic multi-objective optimization Particle swarm optimization Adversarial decomposition
ISSN:	2210-6502
Online-Zugang:	Volltext
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