An efficient spread-based evolutionary algorithm for solving dynamic multi-objective optimization problems

Dynamic multi-objective optimization algorithms are used as powerful methods for solving many problems worldwide. Diversity, convergence, and adaptation to environment changes are three of the most important factors that dynamic multi-objective optimization algorithms try to improve. These factors a...

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Veröffentlicht in:	Journal of combinatorial optimization Jg. 44; H. 1; S. 794 - 849
Hauptverfasser:	Falahiazar, Alireza, Sharifi, Arash, Seydi, Vahid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2022 Springer Nature B.V
Schlagworte:	Adaptation Combinatorics Convergence Convex and Discrete Geometry Evolutionary algorithms Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Multiple objective analysis Mutation Operations Research/Decision Theory Operators Optimization Optimization algorithms Theory of Computation Optimization algorithm Dynamic multi-objective optimization problems Evolutionary algorithm Heating optimization
ISSN:	1382-6905, 1573-2886
Online-Zugang:	Volltext
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