Application of genetic algorithm, a mega-heuristic approach, to solve a real-size vehicle routing problem: a case study

Abstract

Most of the 3PL companies that provide transportation services are handling thousands of orders per day. Vehicle routing problems (VRPs) help plan the distribution of goods with the optimum fleet of vehicles and delivery routes and play an important role in helping businesses reduce transportation costs while ensuring service level. VRPs are NP-hard combinatorial optimization problems. It is quite difficult to achieve an optimal solution for real-size problems with a mathematical modelling approach because of its NP-hard structure. Genetic algorithm (GA) plays a major role in searching for near-optimal solutions for NP-hard optimization problems. This article develops the GA model for VRPs. The result shows that the delivery cost is reduced by 17.88%, while the service level increase from 88.7 to 100%. It indicates that the model can be a good technique for VRPs.