Multi-objective and Multi-product Inventory-location Model under Stochastic Demand

Abstract

This article studies the problem of inventory location for multi-objective and multi-product integrated planning based on existing warehouses. The model constructed in this paper includes two objective functions, minimizing total cost and minimizing transit time, and taking into account three realistic constraints of lead time, minimum order volume, and warehouse capacity. Afterwards, the second-generation genetic algorithm was used to solve the model and the actual case was used to prove that the integrated planning was more cost-effective than the new-build warehouse. And market fluctuations will not have much impact on the results of warehouse planning. Finally, the article validates the constraint conditions and proves that the lead time has a great influence on the warehouse planning results, while the minimum order quantity constraint has little effect on the planning results.