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

Yu Cheng*, Yongjie Jin, Jinglu Hu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages2545-2549
Number of pages5
Publication statusPublished - 2009 Dec 1
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: 2009 Aug 182009 Aug 21

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Country/TerritoryJapan
CityFukuoka
Period09/8/1809/8/21

Keywords

  • Multi-objective optimization
  • NSGA-II
  • Shortest path problem
  • ε-dominance

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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