A Heuristic Hybrid Optimization Approach for Spare Parts and Maintenance Workers Under Partial Pooling

The joint planning of spare parts and maintenance workers in a multiple echelon inventory system with lateral and cross-echelon transshipment can reduce the total cost of the system. However, partial pooling is not extensively considered in the joint optimization problem of maintenance resources. In this paper, the objective is to determine the optimal inventory of spare parts and the number of maintenance workers to minimize the total cost of the system considering partial pooling. First, a greedy heuristic is used to obtain the initial inventory. Then, the cat swarm optimization algorithm is formulated to produce nearly optimal results, which can solve larger instances with a faster computation time. Furthermore, a maintenance system with 4 local warehouses, 3 central warehouses and 1 plant serving 5 machine groups is analyzed, in which each machine consists of 5 key components that can breakdown independently. The results verify the effectiveness of the proposed optimization approach. Finally, the total cost for different resource provision scenarios, failure rates and system parameters are discussed.