Hybrid ant colony optimization and visibility studies applied to a job-shop scheduling problem

J. Heinonen*, F. Pettersson

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

87 Citations (Scopus)

Abstract

A hybrid ant colony optimization (ACO) algorithm is applied to a well known job-shop scheduling problem: MT10 (Muth-Thompson). The ACO tries to preserve and improve existing solutions, and a postprocessing algorithm is applied to the tour of an ant upon its completion. Studies are performed to see what effect visibility has on the outcome with regards to the ACO part of the algorithm.

Original languageEnglish
Pages (from-to)989-998
Number of pages10
JournalApplied Mathematics and Computation
Volume187
Issue number2
DOIs
Publication statusPublished - 15 Apr 2007
MoE publication typeA1 Journal article-refereed

Keywords

  • ACO
  • Ant colony optimization
  • Hybrid
  • Job-shop scheduling
  • Optimization
  • Scheduling

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