Dynamic constrained multi-objective optimization based on adaptive combinatorial response mechanism

In dynamic multi-objective optimization problems (DMOPs), objective functions, problem parameters, and constraints may change over time. Mainly, DMOPs use response mechanisms to generate the initial population after the environment changes. In this research, we develop an adaptive version of the com...

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Veröffentlicht in:	Applied soft computing Jg. 155; S. 111398
Hauptverfasser:	Aliniya, Zahra, Khasteh, Seyed Hossein
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2024
Schlagworte:	Adaptive combinatorial response mechanism Constraint handling technique Dynamic constrained multi-objective optimization Evolutionary algorithm Reinforcement learning Dynamic constrained multi-objective optimization Adaptive combinatorial response mechanism Evolutionary algorithm Reinforcement learning Constraint handling technique
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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