Multi-objective Optimization of E-commerce Logistics Warehouse Layout Based on Genetic Algorithm

With the support of Internet technology and infrastructure construction, fast and convenient online shopping has become an important part of urban consumption. E-commerce has a wide variety of products, large demand, short consumption cycles, and consumers have relatively high time requirements for online shopping services. A good warehouse layout strategy and inventory allocation strategy can help companies shorten inventory and pick-up time, reduce labor costs, and optimize the quality of delivery services. Therefore, studying the layout and distribution of e-commerce logistics warehouses is of inestimable value for improving the market competitiveness of e-commerce enterprises. This paper takes a E-commerce company’s storage center as the object, considers goods’ turnover rate and shelves’ stability as principles to construct a multi-objective optimization mathematical model. By setting up random goal weights to improve traditional genetic algorithm, and to use MATLAB software platform to optimize the solution with mixed multitargets genetic algorithm on basis of the background of a specific warehouse position distribution. The result shows that this model is practical and effective. It can realize the reasonable distribution of the layout problem and reduce handling loss, as well as improve warehouse’s space utilization.