考虑多技能水平工人分配的复杂产品装配调度问题

In the assembly production line of complex aerospace products such as satellites and missiles, many assembly jobs are manually completed by a group of workers collaborating together, and each product requires the same assembly process for completion. Due to variations in the skill levels and assembly efficiency among different workers, as well as multiple optional workstations for each process, the scheduling problem in the complex product assembly workshop can be regarded as a combination of hybrid flow shop scheduling and worker allocation. To address this issue, a multi-objective hybrid flow shop scheduling model considering the allocation of workers with multiple skill levels is constructed in this paper. An improved optimization algorithm called optimizing mutation evolution algorithms is proposed. Firstly, the Nawaz-Enscore-Ham heuristic algorithm is utilized to generate an initial population and enhance the quality of solutions. Secondly, a mutated population is added to the non-dominated sorted population to increase population diversity. Finally, the proposed algorithm is compared with six other multi-objective evolutionary algorithms(MOEAs) based on a case study of a complex aerospace product assembly workshop. The results demonstrate that the proposed algorithm outperforms the other six MOEAs algorithms in terms of approaching the quality of the optimal solution and algorithm stability.