Route Optimization In Delivery Networks Based On A Genetic Algorithm And Milp Approach: A Case Of Best Express

Abstract

The current state of last mile delivery in Vietnam, specifically at Best Express, faces significant challenges in optimizing delivery routes. Currently, shippers at Best Express manually define their delivery routes without the aid of sophisticated optimization tools. This practice leads to inefficient routing, resulting in wasted time and increased operational costs due to non-optimal travel distances. The primary goal of this study is to develop a more efficient routing system that will reduce travel time, decrease overall travel distances, and cut down on operational costs. The research employs Mixed-Integer Linear Programming (MILP) and Genetic Algorithms (GA) as the primary methods for finding the optimal delivery routes. MILP is used to formulate the routing problem mathematically, defining an objective function to minimize total travel distance. GA is utilized to simulate the evolution of potential solutions, iteratively improving route plans through processes inspired by natural selection and genetics, such as crossover and mutation. The results of the study indicate a significant reduction in travel distances compared to the current manually defined routes. The findings suggest that route optimization is crucial for the development and efficiency of the delivery industry. Implementing such optimization techniques can substantially enhance operational efficiency, reduce costs, and improve customer satisfaction. Therefore, it is recommended that logistics companies, including Best Express, adopt advanced optimization tools like MILP and GA to streamline their delivery processes and stay competitive in the rapidly evolving logistics sector.