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...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 22; no. 1; pp. 47 - 60
Main Authors:	Gong, Dunwei, Sun, Jing, Miao, Zhuang
Format:	Journal Article
Language:	English
Published:	IEEE 01.02.2018
Subjects:	Context Convergence Genetic algorithm Genetic algorithms interval many-objective optimization Noise measurement Optimization set-based evolution Sorting Uncertainty
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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