An ant colony optimization heuristic for solving maximum independent set problems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

40 Scopus citations

Abstract

In this paper, ant colony optimization heuristic is extended for solving maximum independent set (MIS) problems. MIS problems are quite different from the travelling salesman problems (TSP) etc., in which no concept of "path or order" exists in its solutions. Based on such characteristics, the ant colony optimization heuristic is modified in this paper in the following ways: (i) a new computation method for heuristic information is adapted; (ii) the pheromone update rule is augmented; (iii) a complement solution construction process is designed. The simulation shows that the proposed ant colony optimization heuristic is effective and efficient for MIS problems.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2003
EditorsLicheng Jiao, Xin Yao, Brijesh Verma, Henry Selvaraj
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages206-211
Number of pages6
ISBN (Electronic)0769519571, 9780769519579
DOIs
StatePublished - 2003
Event5th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2003 - Xian, China
Duration: 27 Sep 200330 Sep 2003

Publication series

NameProceedings - 5th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2003

Conference

Conference5th International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2003
Country/TerritoryChina
CityXian
Period27/09/0330/09/03

Keywords

  • Ant colony optimization
  • Chemicals
  • Computational intelligence
  • Computational modeling
  • Genetic algorithms
  • Graph theory
  • Learning systems
  • Neural networks
  • Process design
  • Traveling salesman problems

Fingerprint

Dive into the research topics of 'An ant colony optimization heuristic for solving maximum independent set problems'. Together they form a unique fingerprint.

Cite this