NDLI: Adaptive epsilon non-dominated sorting multi-objective evolutionary optimization and its application in shortest path problem

Content Provider	IEEE Xplore Digital Library
Author	Yu Cheng Yongjie Jin Jinglu Hu
Copyright Year	2009
Description	Author affiliation: Graduate School of Information, Production and Systems, Waseda University. Hibikino 2-7, Wakamatsu-ku, Kitakyushu-shi, Fukuoka, JAPAN (Yu Cheng; Yongjie Jin; Jinglu Hu)
Abstract	This paper presents an adaptive epsilon non-dominated sorting method for multi-objective evolutionary optimization which has the ability to preserve both the efficiency and diversity. In NSGA-II, a fast non-dominated sorting mechanism is applied to sort solutions in an efficient way. However, it may suffer from deterioration and diversity in population is not as great as expected. To solve this problem, the concept of epsilon-dominance is applied for updating solutions in non-dominate sorted layers according to adaptive epsilon value, and the novel update strategy could prevent deterioration and keep diversity well. A real-world city map with 410 nodes and 1334 arcs is used in experiment, and the result shows that the proposed algorithm (AENSGA) performs better than NSGA-II in multi-objective shortest path problem.
Starting Page	2545
Ending Page	2549
File Size	433706
Page Count	5
File Format	PDF
ISBN	9784907764340
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-18
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE
Subject Keyword	Sorting Shortest path problem Evolutionary computation Production systems Optimization methods Cities and towns Engineering management Pareto optimization Clustering algorithms Computational complexity shortest path problem multi-objective optimization NSGA-II ɛ-dominance
Content Type	Text
Resource Type	Article

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