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

J. Heinonen; F. Pettersson

doi:10.1016/j.amc.2006.09.023

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 journal › Article › Scientific › peer-review

98 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 language	English
Pages (from-to)	989-998
Number of pages	10
Journal	Applied Mathematics and Computation
Volume	187
Issue number	2
DOIs	https://doi.org/10.1016/j.amc.2006.09.023
Publication status	Published - 15 Apr 2007
MoE publication type	A1 Journal article-refereed

Keywords

ACO
Ant colony optimization
Hybrid
Job-shop scheduling
Optimization
Scheduling

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Cite this

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

Abstract

Keywords

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