Blocking Flow Shop Scheduling Based on a Multi-Group Collaborative Sparrow Search Algorithm

The blocking flow shop scheduling problem (BFSP) prevails widely in the process manufacturing industry. In this paper, a multi-group collaborative sparrow search algorithm (MGCSSA) is proposed for minimizing the makespan for BFSP. Firstly, a collaborative initialization strategy is designed to generate initialized populations with certain quality. Second, an elite solution set and a multi-group collaboration mechanism are introduced to improve the adequacy of the global search, and the producer and scrounger position update formulas are improved to increase the population diversity. Then, three neighborhood heuristics are used to locally strengthen individuals in the elite solution set that enhance the ability of the algorithm to jump out of the local optimum. Finally, the proposed algorithm is evaluated experimentally in test cases. The experimental data and comparative results show that the proposed MGCSSA has superior performance and is highly competitive in solving BFSP.