Multi-echelon inventory optimization of spare parts under imperfect maintenance conditions

Considering the constraints of limited maintenance times under imperfect maintenance conditions, the multi-echelon inventory optimization problem of repairable spare parts with scrap process was studied. Based on METRIC model, a multi-echelon inventory optimization model with scrap process was established with the constraint of availability and the optimization goal of costs. In the algorithm design, a Particle Swarm Optimization -Marginal Tabu Search (PSO-MTS) hybrid Algorithm was proposed. In the early stage of the algorithm, PSO algorithm was used to obtain the global high-quality solution quickly, then Tabu Search was entered to develop the local search ability, and the marginal optimization algorithm was used to construct the neighborhood to obtain the optimal solution. The experiment results showed that the proposed approach could solve the multi-echelon inventory optimization problem of spare parts effectively. © 2021, Editorial Department of CIMS. All right reserved.