Paper Info
Title
Using Genetic Algorithms and Heuristics for Job Shop Scheduling with Sequence-Dependent Setup Times
Abstract
The importance of job shop scheduling as a practical problem has attracted the attention of many researchers. However, most research has focused on special cases such as single machine, parallel machine, and flowshop environments due to the “hardness” of general job shop problems. In this paper, a hybrid algorithm based on an integration of a genetic algorithm and heuristic rules is proposed for a general job shop scheduling problem with sequence-dependent setups (Jm|sjk|Cmax?). An embedded simulator is employed to implement the heuristic rules, which greatly enhances the flexibility of the algorithm. Knowledge relevant to the problem is inherent in the heuristic rules making the genetic algorithm more efficient, while the optimization procedure provided by the genetic algorithm makes the heuristic rules more effective. Extensive numerical experiments have been conducted and the results have shown that the hybrid approach is superior when compared to recently published existing methods for the same problem.
Year
DOI
Venue
2001
10.1023/A:1014990729837
Annals OR
Keywords
Field
DocType
scheduling,sequence-dependent setup time,job shop,genetic algorithm,and heuristic
Heuristic,Mathematical optimization,Hybrid algorithm,Job shop scheduling,Fair-share scheduling,Computer science,Job shop,Flow shop scheduling,Rate-monotonic scheduling,Genetic algorithm
Journal
Volume
Issue
ISSN
107
1-4
15729338
Citations 
PageRank 
References 
30
1.31
8
Authors
2
Name
Order
Citations
PageRank
Waiman Cheung175266.77
Hong Zhou2857.92