A Hybrid Differential Evolution Algorithm for Scheduling Parallel Batch Processing Machine with Unequal Job Ready Times

This paper presents a mixed integer linear programming model of scheduling parallel batch processing machines that minimizes total tardiness of jobs. The proposed model incorporates several practical issues such as unequal job ready times, arbitrary job sizes, and arbitrary job processing times. Due to the NP-hardness of problem under study, this paper proposes a hybrid differential evolution (HDE) algorithm to solve large-sized instances. To avoid the premature convergence, simulated annealing is incorporated in HDE to help the algorithm escape from local optima. The performance of presented model and proposed algorithm is verified by extensive experiments. The related results show the effectiveness of the proposed model and HDE for small and large-sized problems. In addition, some statistical tests are conducted to find the best performance of HDE due to its parameters.