Food E-Commerce Logistics Distribution Path Optimization Model Based on Hybrid Genetic Algorithm

Abstract

In order to optimize food logistics distribution path, reduce distribution cost and improve customer satisfaction with product delivery time is the key of food logistics. In view of the poor effect of current food e-commerce logistics distribution path allocation, a food e-commerce logistics distribution path optimization model based on hybrid genetic algorithm is proposed. Considering that the goods carried by food logistics have certain particularity and high requirements for temperature, it is proposed to set a fuzzy time window in food logistics distribution to reflect customer satisfaction. A multi-objective optimization model is established to minimize the distribution costs such as transportation cost, cargo damage cost and time cost and maximize the customer satisfaction with fuzzy time window. The improved genetic algorithm is used to solve the food distribution problem with fuzzy time window. Through experimental analysis, the effectiveness and practical value of the food e-commerce logistics distribution path optimization model based on hybrid genetic algorithm are verified.