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New pheromone trail updating method of ACO for satellite control resource scheduling problem

  • Xi'an Jiaotong University

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

5 Scopus citations

Abstract

An ant colony optimization approach for the satellite control resource scheduling problem is presented. Based on the observation that the solution space of the problem is sparse, two pheromone updating methods, i.e., the reinitialize-guidance-updating and current-guidance-updating methods, are proposed to avoid the trapping in local optima. The basic idea of these two methods is to change the distribution of pheromone trails by updating them with a guidance solution once the algorithm stagnates. We compare the proposed algorithm with several other heuristics. The experimental results demonstrate that our approach is competitive in terms of exploration capability of reaching the near-global optimal solution and adaptability to the future situations.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs
StatePublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain
Duration: 18 Jul 201023 Jul 2010

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Country/TerritorySpain
CityBarcelona
Period18/07/1023/07/10

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