Research on Optimization of Postal Logistics Distribution Driven by Operations Research Algorithms: A Case Study and Comparative Analysis

Based on the vehicle distribution optimization problem with time window in postal logistics, this paper intends to apply various operations research optimization algorithms such as exact algorithms, tabu search algorithm, genetic-simulated annealing algorithm, etc., to optimize a postal delivery network in Guangzhou, China. It employs suitable delivery cost models and programming implementation. The effectiveness of heuristic algorithms is validated using standard instances, followed by further solving of real-world problems using both exact and heuristic algorithms. By comparing the original delivery schemes with the newly proposed solutions, improvement suggestions are provided for the postal delivery network. The research shows that the improved Genetic-Metropolis algorithm can effectively obtain the optimal distribution scheme, and the vehicle travel distance can be greatly reduced compared with that before the improvement, so as to reduce the cost of the transportation process. This paper innovatively introduces the idea of large-scale neighborhood search and simulated annealing to improve the genetic algorithm, which is used to solve the optimization model of mail truck path, but also presents the optimization results more intuitively through the visualization technology of location data.