Multiobjective Planning for Logistics Distribution of Consumer Electronic Items Based on Improved Genetic Algorithm

Abstract

With the increasing uncertainty of customer demand, order management that takes into account the uncertainty of customer demand is important in the supply chain between distribution bases (distribution centers, RDCs, etc.) and large retailers. A multisite delivery planning system is recommended to scale past to handle a single product. Aiming at the logistics distribution problem of consumer electronic products, the problem is attributed to a multiobjective optimization problem, and an improved genetic algorithm is used to deal with it. Combined with the situation, this paper proposes a multiproject (multiproject delivery mass production planning system) and studies the narrative problem description, formula, solution sequence, and case analysis results. The experimental results show that this method can effectively improve the logistics distribution efficiency by 18% and reduce the distribution cost by 34%, by finding the optimal distribution path, reducing the total cost of low-carbon distribution of fresh products, improving customer satisfaction, reducing energy consumption, and achieving economic and social benefits for enterprises.