Route Optimization based on Clustering and Travelling Salesman Problem

Abstract

The rapid pace of e-commerce growth has affected the logistics sectors to face challenges such as the pressure of consumer expectations and increased competition regionally across all players in the supply chain. This e-commerce wave has led the logistics sector to struggle to improve logistics distribution efficiency and reduce operating costs to keep up with consumers' fastgrowing demand simultaneously. Therefore, this paper aims to introduce The Route Optimization approaches that are developed to enhance the efficiency of the day-to-day operation in the logistics industry at one leading distribution company, CV. Berkah Express in Palembang, South of Sumatera, Indonesia. The system aims to optimize the last-mile distribution route by reducing the driver's travel distance to drive more efficiently. In this paper, comparison results between the original route taken by the driver and the proposed route based on optimization are conducted and reported. The unsupervised learning result was also achieved and reported in comparison results. Based on the comparison result, the route optimization system was proved effective through example analysis on the said test dataset. The analysis results also reflect how the system's algorithm can provide better routing solutions with shorter distances and lesser time that could decrease the last-mile distribution costs efficiently