Shortest Route Optimization for Waste Collection Using ACO-Based CVRP : Case Study of Banjar Basa and Banjar Tembau, Marga

Ida Bagus Kade Puja Arimbawa K; I Gusti Ayu Novitasari; Putu Nanda Andika Permana

doi:10.24843/JMAT.2026.v16.i01.p194

Authors

Ida Bagus Kade Puja Arimbawa K Universitas Bali Dwipa
I Gusti Ayu Novitasari Faculty of Humanities and Social Science, Bali Dwipa University, Indonesia
Putu Nanda Andika Permana Faculty of Technology and Health Sciences, Bali Dwipa University, Indonesia

DOI:

https://doi.org/10.24843/JMAT.2026.v16.i01.p194

Keywords:

Ant Colony Optimization (ACO), Capacitated Vehicle Routing Problem (CVRP), Waste Collection, Route Optimization, Marga Village

Abstract

The increasing volume of household waste in rural areas has created challenges in transportation management, particularly in determining efficient waste collection routes. This study aims to optimize waste transportation routes in Marga Village, Tabanan Regency, focusing on Banjar Basa and Banjar Tembau, which have distinct topographical and settlement characteristics. The optimization process was formulated as a Capacitated Vehicle Routing Problem (CVRP) and solved using the Ant Colony Optimization (ACO) algorithm. The research began by modeling the waste collection points as graph vertices, with roads serving as edges weighted by distance. Simulation results showed that Banjar Basa, which has a larger area and more collection points, required two trips to cover all nodes, whereas Banjar Tembau required only one trip due to its smaller and denser topology. The ACO algorithm successfully identified the shortest and most efficient route configuration, with pheromone updates guiding the convergence toward the global optimum. The combination of parameters yielded stable convergence and effective route minimization. These results demonstrate that ACO is a robust and adaptive approach for optimizing waste transportation systems in rural regions, offering a sustainable solution for reducing operational costs and improving environmental quality.

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