Route Optimization for Perishable Goods Distribution Using Ant Colony Optimization: A Capacitated Vehicle Routing Problem (CVRP) Case Study

Ramdan, Deni Muhamad
Hartati, Verani

Electronic Journal of Education, Social Economics and Technology
Vol 6, No 1 (2025)

This study addresses inefficiencies in route planning for the distribution of perishable goods by a small-scale enterprise, Jaya Abadi Fruits, located in East Jakarta. The current manual delivery planning, reliant on driver experience, results in suboptimal distances, increased fuel usage, and inconsistent service quality. To overcome these challenges, the Ant Colony Optimization (ACO) algorithm was applied to a Capacitated Vehicle Routing Problem (CVRP) and implemented using MATLAB. The model incorporates real-world parameters such as delivery distances, box dimensions, demand volume, and vehicle capacities. Simulation results demonstrate significant improvements: for Vehicle 1, travel distance and distribution cost were reduced by 41.93% and 15.6%, respectively; for Vehicle 2, distance decreased by 30.96% and cost by 2.03%. These findings validate ACO as an effective, low-cost, and scalable decision-support tool for logistics operations in small enterprises lacking integrated digital infrastructure. The research contributes to the optimization of last-mile delivery in resource-limited supply chains, particularly in emerging economies.