Application of vehicle routing problem with time windows on optimizing distribution network: A case study of gemadept corporation

Abstract

This paper proposes a genetic algorithm approach to the vehicle routing problem with time windows (VRPTW). The VRPTW is a well-known combinatorial optimization problem in which a fleet of vehicles must serve a set of customers within predefined time windows while minimizing the total travel distance. The problem is applied into a case study of Gemadept company where the staff plans the routes manually and suffer much lost due to inaccuracy. The raw data was processed by Python to replace the manual arrangement of the staff, then the model was solved by CPLEX to find the optimum solution for the vehicle routine, and the results are analyzed through sensitivity analysis. The proposed approach is expected to have important practical applications in the transporting process of the company, where efficient routing and scheduling of vehicles can lead to significant cost savings and improved service quality.