A batch splitting job shop scheduling problem with bounded batch sizes under multiple-resource constraints using genetic algorithm

Considering alternative resources for operations, requirement of multiple resources to process an operation and a jobpsilas batch size greater than one in the real manufacturing environment, a study is made on the batch splitting scheduling problem with bounded batch sizes under multiple-resource constraints, based on the objective to minimize the maximum completion time. A genetic algorithm which is suitable for this problem is proposed, with a new chromosome representation, which takes into account the batch splitting of the original batches of jobs. And a new crossover method and a new mutation method are proposed based on the new chromosome representation. The results of the simulation indicate that the method is feasible and efficient.