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Cahyo, Rahandya
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Computer Science & IT

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Implementasi Ant Colony Optimization Untuk Rute Terpendek Pada Pengiriman Barang J&T Cahyo, Rahandya; Siregar, Alda Cendekia; Octariadi, Barry Ceasar
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10467

Abstract

Parcel delivery is a logistics service that requires speed and efficiency, especially in determining delivery routes. The choice of this topic is based on the problem faced by J&T delivery in Kubu Raya, particularly Desa Kapur, where long travel distances often result in inefficiency. This study applies the Ant Colony Optimization (ACO) algorithm to identify the shortest route for parcel delivery. ACO mimics the behavior of ants in finding optimal paths based on pheromone intensity. Location data were obtained using coordinates from the Google Maps API and modeled into a weighted graph, where nodes represent delivery points and edges represent distances. The optimization process was carried out by simulating the movement of ant agents to evaluate alternative routes, followed by pheromone updates on the more efficient paths. The results indicate that ACO successfully generated more efficient delivery routes compared to conventional methods, achieving a distance reduction of 28.29%, equivalent to approximately 10.68 km saved. This efficiency contributes to reduced travel time and operational costs. The optimized routes were also visualized through an interactive map using Leaflet.js to facilitate analysis and interpretation. Therefore, ACO is proven to be effective in optimizing delivery routes and has strong potential for real-world application in courier services.
Co-Authors Octariadi, Barry Ceasar Siregar, Alda Cendekia