Research on E-commerce Supply Chain Inventory Optimization and Multi-Objective Planning with Database Technical Support

This paper first describes the basic theoretical knowledge of supply chain inventory control and analyzes the existing supply chain inventory control strategies.For the relationship between safety stock and customer service level and inventory cost, the safety stock factor is used as a decision variable, and a supply chain multilevel inventory control model is established under (t,s,S) inventory replenishment strategy.Secondly, the selection operator, crossover operator and mutation operator of the traditional genetic algorithm are adaptively improved, and an improved multi-objective adaptive genetic algorithm is proposed, and this algorithm is used to solve the inventory optimization with the two objectives of supply chain inventory cost and customer service level.The simulation results of the algorithm show that the improved genetic algorithm has better convergence and the obtained Pareto optimal solution set is closer to the real optimal frontier.When the IGD value is minimized and kept constant, the convergence speed of this paper's algorithm (34 times) is 38.18% lower than that of the traditional genetic algorithm (55 times), and the model converges faster while its Pareto solution set is more uniformly distributed.Example results also show that using the model in this paper can reduce the inventory of each node in the supply chain system and reduce the transportation cost.