Multi-objective Collaborative Optimization of Multi-level Inventory: A Model Driven by After-Sales Service

To improve the quality of after-sale service that is a new aspect for all manufacturing enterprises, the allocation of inventory reserves as well as reasonable dispatch between inventories have become the key to meet customer demand and reduce inventory cost. In this paper, a multi-stage safety inventory optimization model is constructed for after-sales service demand. The order quantity of inventory in the model is set to consider the changes of customer demand and fault loss under the influence of different quarters and regions. The cost and transportation time are also optimized by using multi-objective particle swarm optimization algorithm at the same time. Simulational results show that the proposed model can not only respond to the demand changes in different regions and different quarters timely, but also reduce the cost and time loss to meet customer demand. Compared with the methods that merely considers time and cost respectively, the proposed model is more suitable to solve the multi-stage inventory optimization problem across regions.