New parallel algorithm based on DE for batch splitting job shop scheduling under multiple-resource constraints

To provide a practical method for production scheduling in flexible manufacturing system, based on the objective to minimize the makespan, the batch splitting job shop scheduling problem is studied under multiple-resource constraints. A scheduling model is established based on equal-sized batch splitting, and a new parallel algorithm is proposed to solve both the batch splitting problem and the batch scheduling problem based on a parallel chromosome representation, with a global search method based on self-adaptive differential evolution(DE). An Interchange-based local search method is further designed to gain a better performance. A solution consists of the optimum number of sub-bathes for each job, the optimum batch size for each sub-batch and the optimum sequence of operations for sub-batches. The simulation results show the effectiveness and feasibility of the algorithm.