Research on the Optimization of Fresh Agricultural Products Trade Distribution Path Based on Genetic Algorithm

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.

Optimizing Fresh Agricultural Product Distribution Paths Under Demand Uncertainty

“…In addition to the quantity deterioration rate, the delivery time is an important indicator to measure the service quality in the VRP for FAPs (Sun et al, 2022). An early or late delivery can result in the reduction of consumer satisfaction and, thus, incur penalty costs.…”

“…The rapid reduction in FAPs quality during transportation requires they be delivered within consumer-specified times or time windows. Early or delayed delivery will result in lower consumer satisfaction with logistics service quality (Sun et al, 2022).…”

Digital Innovations in Agriculture

“…In the thirty-fourth article [41], a multi-objective logistic distribution path optimization model with time constraints was constructed, and a genetic algorithm was used to optimize the commercial distribution path for fresh agricultural products. Combining the genetic algorithm with a real case to be studied, the study aimed to solve enterprises' narrow distribution paths and promote the model's application to similar enterprises with similar characteristics.…”

Research on fresh food delivery path optimization based on genetic combined with greedy algorithm

“…Zhu Xiaohong [3] used three research methods, namely literature analysis, survey analysis and comparative research, to analyze the current situation of fresh produce distribution in Huizhou City, put forward some outstanding problems and proposed an optimization path. Yang Junzi [4] used Dijkstra's algorithm to establish a mathematical model of vegetable distribution in an area of Hengshui city, to find out the shortest distribution route for the community and give the optimal solution. Cheng Yu [5] chose genetic algorithm as the algorithm for solving the path optimization model in this paper.…”