Optimization of Heterogeneous Vehicle Routing Problem Using Genetic Algorithm in Courier Service

Current technological developments triggered the public to use e-commerce platforms as providers of transactions. This resulted in an increase in the courier service business for shipping goods to customers. The types of goods processed through courier services are very diverse and shipments that are processed by courier services continue to increase. In previous studies only discussed the delivery using homogeneous vehicles, without grouping and the number of shipments is limited. This study aims to minimize the route and the number of heterogeneous vehicles serving more than 1,500 shipments per day by courier service. Therefore, in this study is based on the VRP concept of heterogeneous vehicles to minimize route and courier service vehicles. The use of the K-Means cluster method in this study aims to classify customers, minimize delivery distance and shorten the computation time. Genetic Algorithm (GA) based approach is applied by using the criteria of many generations to be achieved and the difference in efficiency rates between generations to get the results of route optimization and courier service vehicles.