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

被引：66

作者：

Heinonen, J. ^{[1
]}

Pettersson, F. ^{[1
]}

机构：

[1] Abo Akad Univ, Tech Fac, Heat Engn Lab, SF-20500 Turku, Finland

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2007年 / 187卷 / 02期

关键词：

ant colony optimization; ACO; job-shop scheduling; scheduling; optimization; hybrid;

D O I：

10.1016/j.amc.2006.09.023

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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. (C) 2006 Elsevier Inc. All rights reserved.

引用

页码：989 / 998

页数：10

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