Parallel service mode of production and inventory for spare part inventory optimization

Previous studies on inventory adopt the serial supply mode of from production to inventory to customer demand , that is, at the end of the previous period, the spare parts requirements predicted for the next period need to be ready. Trying to cancel the preparation of some spare parts in the previous period and transfer them to the production resources in the next period, the capital occupation and inventory holding cost incurred by these spare parts can be reduced. Therefore, we propose a parallel service mode of production and inventory for inventory optimization, in which production resources are arranged from the scheduling level and cooperate with inventory to meet customer demands. By introducing virtual warehouses that each contains infinite spare parts, the problem of inventory optimization is transformed into a scheduling problem with objectives of minimum inventory capital occupation and minimum total cost including inventory holding cost, transportation cost and tardiness cost. The optimal inventory setting of each actual warehouse is determined based on the usage of spare parts in each corresponding virtual warehouse in the optimal scheduling solution. To obtain the optimal scheduling solution, an evolutionary algorithm is proposed, in which a modified idle time insertion method and five problem-specific knowledge-guided local search operators are developed. Numerous experiments are conducted and the results demonstrate the effectiveness of the proposed algorithm compared with other well-known algorithms. Furthermore, the superiority of the parallel service mode compared with the serial supply mode is verified.(C) 2022 Elsevier B.V. All rights reserved.

Automated summary

Previous studies on inventory adopt a serial supply mode, while this study proposes a parallel service mode to optimize inventory. By introducing virtual warehouses with infinite spare parts, the inventory optimization problem is transformed into a scheduling problem, and an evolutionary algorithm is used to obtain the optimal solution. Experimental results demonstrate the effectiveness of the proposed algorithm and verify the superiority of the parallel service mode.