DocumentCode :
2633775
Title :
An ant colony optimization approach for no-wait flow-line batch scheduling with limited batch sizes
Author :
Wang, Xiao-Rong ; Wu, Tie-Jun
Author_Institution :
Inst. of Intelligent Syst. & Decision Making, Zhejiang Univ., Hangzhou, China
Volume :
3
fYear :
2003
fDate :
9-12 Dec. 2003
Firstpage :
2959
Abstract :
A novel ant colony optimization (ACO) algorithm, ACO-BAT, was presented for the no-wait flow-line batching and scheduling problem, where the jobs are partitioned into groups, jobs of the same group can be processed simultaneously as a batch by the batch processing machines, but with limited batch size. The batch-sequence-dependent setup time of the batch processing machines, and the batch transfer time are considered in the problem. In the ACO-BAT algorithm, the artificial ants iteratively construct feasible job batching and batch sequencing solutions, guided by the pheromone distributed in the solution space. Comparisons with other algorithms on the extended Taillard´s benchmark problems show that our algorithm is very efficient and robust.
Keywords :
batch processing (industrial); flow shop scheduling; metalworking; optimisation; ant colony optimization; batch processing machines; batch transfer time; flow-line batching; metalworking industry; scheduling problem; Ant colony optimization; Circuit testing; Decision making; Intelligent systems; Iterative algorithms; Job shop scheduling; Laboratories; Partitioning algorithms; Routing; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-7924-1
Type :
conf
DOI :
10.1109/CDC.2003.1273076
Filename :
1273076
Link To Document :
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