A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization

Both convergence and diversity are crucial to evolutionary many-objective optimization, whereas most existing dominance relations show poor performance in balancing them, thus easily leading to a set of solutions concentrating on a small region of the Pareto fronts. In this paper, a novel dominance...

Celý popis

Podrobná bibliografia

Vydané v:	IEEE transactions on evolutionary computation Ročník 23; číslo 2; s. 331 - 345
Hlavní autori:	Tian, Ye, Cheng, Ran, Zhang, Xingyi, Su, Yansen, Jin, Yaochu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Balancing Convergence diversity Dominance evolutionary algorithm Evolutionary algorithms Evolutionary computation Genetic algorithms many-objective optimization Multiple objective analysis Optimization Pareto dominance Pareto optimization Production scheduling
ISSN:	1089-778X, 1941-0026
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!