A Comparison of Destination Clustering using Density-based Algorithm on The Trip Planning Optimization for Last-Mile Parcel Delivery
Abstract
This study examines the pipeline for real-world delivery trip planning optimization. The study focuses on the capacitated vehicle routing problems. Density-based clustering algorithms were applied prior to resolving the capacitated vehicle routing problem (CVRP) to reduce processing time and to maintain acceptable efficiency. The experimental results with 25 CVRP pipelines were compared. The results showed that the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) method achieved the highest performance. It could reduce the time of trip planning by 30-40% and total distance by 2.2% compared with the traditional method.
Authors: Issaret Prachitmutita, Praisan Padungweang, Olarn Rojanapornpun