Abstract:
Aiming at the complexity and variety of production modes in the actual production system, this paper investigates the hybrid flowshop lot-streaming scheduling problem with batch processing. A variable batching method is proposed by considering the capacity of batch machine and the processing ability of unrelated machines. A scheduling model is established to minimize the completion time via dynamic continuous processing strategy. At the same time, a discrete water wave optimization (DWWO) is proposed to solve the scheduling model. According to the characteristic of batching and optimization objectives, four decoding methods are designed to optimize the machine selection and processing sequence of jobs. By the block optimal insertion, cross operation, and multi neighborhood search, the operation operators are improved for enhancing the local search ability. Moreover, an operation of replacing inferior solution is proposed to improve the convergence ability of the proposed algorithm. Finally, the experimental design method is used to calibrate the parameters of DWWO, and different scale examples are designed to evaluate the performance of DWWO. It is shown via the experimental results that the proposed DWWO algorithm can effectively deal with the hybrid flowshop lot-streaming scheduling problem with batch processing.