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T. F. Abdelmaguid, “Permutation-Induced Acyclic Networks for the Job Shop Scheduling Problem,” Applied Mathematical Modeling, Vol. 33, No. 3, 2009, pp. 1560-1572. doi:10.1016/j.apm.2008.02.004

has been cited by the following article:

• TITLE: Representations in Genetic Algorithm for the Job Shop Scheduling Problem: A Computational Study

  AUTHORS: Tamer F. Abdelmaguid

  KEYWORDS: Job Shop Scheduling, Genetic Algorithm, Mathematical Models, Genetic Representation

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.3 No.12, December 31, 2010

  ABSTRACT: 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.