标题:
Representations in Genetic Algorithm for the Job Shop Scheduling Problem: A Computational Study
作者:
Tamer F. Abdelmaguid
关键词:
Job Shop Scheduling, Genetic Algorithm, Mathematical Models, Genetic Representation
期刊名称:
Journal of Software Engineering and Applications,
Vol.3 No.12,
December
31,
2010
摘要: Due to the NP-hardness of the job shop scheduling problem (JSP), many heuristic approaches have been proposed; among them is the genetic algorithm (GA). In the literature, there are eight different GA representations for the JSP; each one aims to provide subtle environment through which the GA’s reproduction and mutation operators would succeed in finding near optimal solutions in small computational time. This paper provides a computational study to compare the performance of the GA under six different representations.