A hybrid discrete cuckoo search for distributed permutation flowshop scheduling problem

With the development of global manufacturing, the distributed scheduling problems have caught increasing attention recently. In this paper, a hybrid discrete cuckoo search (HDCS) algorithm is proposed to solve the distributed permutation flowshop scheduling problem (DPFSP). In the HDCS, the permutation based encoding scheme is adopted and the earliest completion factory rule is employed to map the individuals into feasible schedules. To implement Lévy flight, a specific variable neighborhood search (VNS) is designed according to the characteristics of the DPFSP. In addition, to avoid premature convergence, the regenerating scheme is employed. To enhance the exploitation ability, several local search operators with respect to the critical factory are designed for the promising individuals. For the HDCS, the influence of parameter setting in solving the DPFSP is investigated. Besides, numerical simulations based on 420 small-sized instances and 720 large-sized instances are carried out. The results compared with several existing algorithms demonstrate the effectiveness of the proposed HDCS.