Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City)

Abstract

Fuel distribution optimization is crucial to meet growing demand and reduce operational costs, especially in cities like Malang, where vehicle numbers are increasing. This research addresses the distribution challenges of PT Pertamina, focusing on designing efficient routes to minimize distance, cost, and delivery time while meeting fuel demands effectively. The problem, classified as a Capacitated Vehicle Routing Problem (CVRP), is solved using the Clarke-Wright Savings (CWS), Nearest Neighbour (NN), and Goal Programming (GP). The CWS is applied to group routes efficiently by reducing travel distances, while NN determined the delivery sequence within each route. GP addressed multi-objective optimization, minimizing costs and delivery time, maximizing Pertashop demands, and optimizing vehicle use. The results show that the combination of CWS and NN algorithms reduced the total travel distance by 140 km, or 12.5% reduction. Additionally, the GP method optimized vehicle use to 13, achieving a 59.68% cost reduction and a 48.68% time savings. These findings highlight the effectiveness of combining these algorithms in fuel distribution optimization, providing a more efficient solution compared to existing routes. Moreover, this approach is adaptable to similar logistics problems, offering a foundation for further research in multi-objective optimization for distribution systems.