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

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 suc-ceed in finding near optimal solutions in small computational time. This paper provides a computational study to com-pare the performance of the GA under six different representations.