Research on the Optimization of Fresh Agricultural Products Trade Distribution Path Based on Genetic Algorithm
Jun Sun, Tianhang Jiang, Yu‐Fei Song, Hao Guo, Yushi Zhang
Abstract
This study, taking the R fresh agricultural products distribution center (R-FAPDC) as an example, constructs a multi-objective optimization model of a logistics distribution path with time window constraints, and uses a genetic algorithm to optimize the optimal trade distribution path of fresh agricultural products. By combining the genetic algorithm with the actual case to explore, this study aims to solve enterprises’ narrow distribution paths and promote the model’s application in similar enterprises with similar characteristics. The results reveal that: (1) The trade distribution path scheme optimized by the genetic algorithm can reduce the distribution cost of distribution centers and improve customer satisfaction. (2) The genetic algorithm can bring economic benefits and reduce transportation losses in trade for trade distribution centers with the same spatial and quality characteristics as R fresh agricultural products distribution centers. According to our study, fresh agricultural products distribution enterprises should emphasize the use of genetic algorithms in planning distribution paths, develop a highly adaptable planning system of trade distribution routes, strengthen organizational and operational management, and establish a standard system for high-quality logistics services to improve distribution efficiency and customer satisfaction.