Joint optimization of integrated mixed maintenance and distributed two-stage hybrid flow-shop production for multi-site maintenance requirements

Abstract

Similar to the synergy of machines and workers in the production process, a perfect operation and maintenance (O&M) service can be implemented only when spare parts and service workers are available at the same time. Considering the production of spare parts and the limited number of workers, a collaborative optimization problem of spare parts production and worker arrangement driven by O&M is proposed in this paper. Specifically, in view of the characteristics that distributed hybrid flow-shops are often encountered in the industrial environment and one O&M activity can be completed by one worker or two workers jointly, spare parts are produced in distributed two-stage hybrid flow shop, and worker service adopts a mixed mode of one worker and two workers. To obtain a satisfactory joint optimization scheme of spare parts and workers, this paper first establishes a mixed integer programming model with dual objectives: the total weighted earliness/tardiness penalty and the number of lost orders. Then, an improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is proposed to solve it. In INSGA-II, an initialization rule, an initialization optimization strategy and three local search operators are designed. Next, to give full play to the best performance of the algorithm, the key parameters are set by a full factor experiment. Finally, extensive experiments are carried out to verify that INSGA-II has good advantages in solving the problem studied.