Research on Multi-objective Slotting Optimization of E-commerce Warehousing Centers Based on Non-dominated Genetic Algorithm

Goods storage is an important function of a warehouse center, and the core processes of goods storage are the storage and shelving of goods, as well as order picking and outbound. The reasonable allocation of storage locations will play a decisive role in these two core processes. Based on the consideration of the work intensity and safety of homework employees, starting from the actual distribution of warehouse locations in e-commerce warehousing centers, a multi-objective warehouse location optimization model was established with the objectives of minimizing the energy consumption of goods entering and leaving the warehouse at a certain moment, maximizing the overall stability of shelves, and maximizing the efficiency of order picking. The Apriori algorithm was used to explore the association rules between goods, and the NSGA-II algorithm combined with TOPSIS method was used to solve the model and obtain the final warehouse location allocation plan. According to the calculated results, the comprehensive benefits of the random location allocation strategy commonly used in e-commerce warehousing have been greatly improved, and all target values have decreased, verifying the effectiveness of the non-dominated sorting genetic algorithm in solving the optimization problem of warehouse locations in e-commerce warehousing centers.