Optimization of J&T Express Manado Courier Distribution Route Using Coordinate-Based Travelling Salesman Problem Method

Abstract

In the package delivery industry, exemplified by J&T Express Manado, optimizing courier distribution routes is essential for customer satisfaction, cost reduction, and on-time deliveries. The Traveling Salesman Problem (TSP) is a valuable tool for finding efficient routes to visit all delivery points once. This study employed the Genetic Algorithm and Nearest Neighbor Algorithm to tackle the TSP, aiming to identify the shortest routes and minimize distribution distances for J&T Express Manado's couriers using geographical coordinates. The Genetic Algorithm resulted in a distribution route of 41.20678 km, while the Nearest Neighbor Algorithm achieved a shorter route of 38.10361 km. For J&T Express Manado, our findings indicate that the Nearest Neighbor Algorithm excels in identifying the shortest courier distribution route and requires significantly less computational time. This study offers insights for J&T Express Manado and similar courier services, enabling them to enhance distribution operations, potentially reducing costs and improving efficiency. It also underscores the practical advantages of the Nearest Neighbor Algorithm in addressing TSP challenges within the industry