A Set-Based Genetic Algorithm for Interval Many-Objective Optimization Problems

Interval many-objective optimization problems (IMaOPs), involving more than three objectives and at least one subjected to interval uncertainty, are ubiquitous in real-world applications. However, there have been very few effective methods for solving these problems. In this paper, we proposed a set...

Celý popis

Podrobná bibliografia

Vydané v:	IEEE transactions on evolutionary computation Ročník 22; číslo 1; s. 47 - 60
Hlavní autori:	Gong, Dunwei, Sun, Jing, Miao, Zhuang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.02.2018
Predmet:	Context Convergence Genetic algorithm Genetic algorithms interval many-objective optimization Noise measurement Optimization set-based evolution Sorting Uncertainty
ISSN:	1089-778X, 1941-0026
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!