Multiobjective Optimization and Hybrid Evolutionary Algorithm to Solve Constrained Optimization Problems

This paper presents a novel evolutionary algorithm (EA) for constrained optimization problems, i.e., the hybrid constrained optimization EA (HCOEA). This algorithm effectively combines multiobjective optimization with global and local search models. In performing the global search, a niching genetic...

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Vydané v:	IEEE transactions on systems, man and cybernetics. Part B, Cybernetics Ročník 37; číslo 3; s. 560 - 575
Hlavní autori:	Wang, Yong, Cai, Zixing, Guo, Guanqi, Zhou, Yuren
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2007
Predmet:	Acceleration Algorithms Artificial Intelligence Benchmark testing Biological Evolution Clustering algorithms Computer Simulation Constrained optimization Constraint optimization Convergence evolutionary algorithm (EA) Evolutionary computation Genetic algorithms global search local search Mathematical Computing Measurement Models, Genetic Models, Theoretical multiobjective optimization Partitioning algorithms Robustness
ISSN:	1083-4419
On-line prístup:	Získať plný text
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