An Improved Ant Colony Algorithm for Multi-objective Flexible Job Shop Scheduling Problem

被引：0
|
作者：
Li, Li [1 ]
Wang, Keqi [2 ]
机构：
[1] NE Forestry Univ, Informat & Comp Engn Coll, Harbin, Heilongjiang, Peoples R China
[2] NE Forestry Univ, Forestry Engn Automat Discipline, Harbin, Heilongjiang, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS ( ICAL 2009), VOLS 1-3 | 2009年
关键词：
Multi-objective Optimization; Flexible Job Shop Schedule; Ant Colony Algorithm; SHIFTING BOTTLENECK; GENETIC ALGORITHM; OPTIMIZATION; SEARCH;
D O I：
10.1109/ICAL.2009.5262833
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Flexible job shop scheduling problem is a very important research in the field of combinatorial optimization. An improved ant colony algorithm for multi-objective flexible job shop scheduling problem is presented in this paper. The rule of our algorithm is described from the following aspects: local update, global update, trail intensities, solution set, local search, suitable parameters. The algorithm we presented is validated by practical instances. The results obtained have shown the proposed approach is feasible and effective for the multi-objective flexible job shop scheduling problem.
引用
收藏
页码：697 / +
页数：2
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