Ant colony optimization for job shop scheduling problem

被引：0
|
作者：
Ventresca, M [1 ]
Ombuki, B [1 ]
机构：
[1] Univ Guelph, Dept Comp Sci & Informat Sci, Guelph, ON N1G 2W1, Canada
来源：
PROCEEDINGS OF THE EIGHTH IASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING | 2004年
关键词：
job shop scheduling; metaheuristic; ant colony optimization; Foot Stepping;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents an application of the Ant colony optimization metaheuristic to the job shop scheduling problem. A pheromone alteration strategy which improves the basic ant system by utilizing the behaviour of artificial ants is introduced. Experiments using well-known job shop problems show that this approach improves on the solution quality obtained by the basic ant system and is competitive with another recently proposed extension of the ant system, the MAX-MIN algorithm.
引用
收藏
页码：28 / 34
页数：7
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