The openshop batch processing problem with non-identical processing times, using simulated annealing and genetic algorithms approaches

This paper addresses batch processing problem on the multimachine openshop. In the batch processing problem, jobs are categorized into batches and the batches are processed by machines. The processing time of each batch equals the maximum processing time of the batch jobs. The objective is to minimize the makespan. We assume non-identical processing time jobs. We used metaheuristic algorithms, including simulated annealing and genetic algorithms to solve the problem. Several numerical experiments show that for the small size problems, the proposed methods generate the solutions by no deviation or a little deviation from the global optimum. Furthermore, for the large-size problems, the proposed methods generate better solutions in a few times as compared to the commercial optimization software Lingo 8.