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All Journal Jupe-Jurnal Pendidikan Ekonomi Hearty : Jurnal Kesehatan Masyarakat Building of Informatics, Technology and Science Academia Open Sewagati: Jurnal Pengabdian Masyarakat Indonesia
Fitria Novitasari
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Journal : Academia Open

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Route Optimization Using Ant Colony for Three-Wheel Vehicle Delivery: Optimasi Rute Menggunakan Koloni Semut untuk Pengiriman Kendaraan Roda Tiga Novitasari, Fitria; Aryanny, Enny
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.11192

Abstract

General Background: Efficient distribution systems are essential in logistics, especially in geographically complex regions like Indonesia. Specific Background: PT. Sinar Genta Logistik distributes three-wheeled Viar motorcycles using double-deck trucks but has not yet optimized its delivery routes. Knowledge Gap: Although the Ant Colony Optimization (ACO) method has been widely applied in solving distribution problems, its application in routing three-wheeled vehicle shipments with fleet capacity constraints using real industry data is limited. Aims: This study aims to optimize delivery routes to reduce travel distance and improve route allocation by applying the ACO algorithm. Results: Using Python programming on Google Colab, the ACO method reduced the total travel distance from 1,849.8 km to 1,556.5 km—a reduction of 293.3 km or 15.86%. The new routing model reorganized deliveries into six vehicle routes adjusted to truck capacity. Novelty: The research applies ACO specifically for the distribution of Viar three-wheeled vehicles with real-world data, integrating Google Maps-based routing and considering capacity constraints. Implications: The findings offer a practical solution for logistics firms to decrease operational distance and adopt algorithm-based distribution strategies for cost efficiency and timely deliveries. Highlights: ACO reduced total delivery distance by 15.86%. Delivery restructured into six efficient routes. Uses real company data and Python-based ACO. Keywords: Ant Colony Optimization, Vehicle Routing Problem, Logistics, Fleet Capacity, Viar
Co-Authors - Ngadiman Amira Nadhifa Rahma Anita Wulandari Elin Haerani Enny Aryanny Fitri Insani Holanda, Helen Imania, Syaila Jasril Jasril Luky Widiya Nafarinda Luthfi Rahman Luthfia Ihza Hafidha Marcella, Eveline Nazir, Alwis Nor Auliya Pebriyanti, Sindi Pratami, Intan Shinta Fauziah Sri Sumaryati