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 f...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.展开更多
文摘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.