Generalized Cyclic Open Shop Scheduling and a Hybrid Algorithm

In this paper, we first introduce a generalized version of open shop scheduling (OSS), called generalized cyclic open shop scheduling (GCOSS) and then develop a hybrid method of metaheuristic to solve this problem. Open shop scheduling is concerned with processing n jobs on m machines, where each job has exactly m operations and operation i of each job has to be processed on machine i. However, in our proposed model of GCOSS, processing each operation needs more than one machine (or other resources) simultaneously. Furthermore, the schedule is repeated more than once. It is known that OSS is NP-hard. Therefore, for obtaining a good solution for GCOSS, which is obviously NP-hard, a hybrid algorithm is also developed. This method is constructed by hybridizing ant colony optimization (ACO), beam search and linear programming (LP). To verify the accuracy of the method, we also compare the results of this algorithm with the optimal solution for some special problems.