Minimizing makespan in a single batch machine using genetic algorithm

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Ho Jin Kai, Yasothei Suppiah, Ajitha Angusamy, Goh Wei Wei, Noradzilah Ismail


This paper deals with a single batch machine scheduling problem to minimize makespan with the consideration of sequence dependent setup time. As the problem is NP hard, a genetic algorithm is developedto provide a solution to this problem. Furthermore, dispatching heuristics such as shortest processing time (SPT), longest processing time (LPT), smallest job size (SJS) and largest job size (LJS) are developed to provide initial solutions to the genetic algorithm. All the developed algorithms and simulation are done using Spyder (Python 3.8) software. Computational results show that the genetic algorithm has outperformed the dispatching heuristics in minimizing the makespan.

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