Septia Anggraini (1), Enny Aryanny (2)
General Background: Efficient route planning is a fundamental aspect of logistics, directly impacting operational costs, fuel consumption, and customer satisfaction. Specific Background: A logistics company based in Batam has been facing inefficiencies in spare part delivery operations due to suboptimal routing strategies. Knowledge Gap: While various routing solutions exist, few are tailored to accommodate dynamic, real-world constraints such as vehicle capacity and varying delivery points in mid-scale logistics operations. Aim: This study aims to optimize delivery routes using the Ant Colony Optimization (ACO) algorithm by modeling the problem as a Vehicle Routing Problem (VRP) with specific operational constraints. Results: The implementation of ACO significantly reduced total travel distance compared to the company’s existing manual routing approach. As a result, fuel consumption was lowered, delivery times improved, and customer service enhanced. Novelty: Unlike generic routing systems, the proposed ACO-based model dynamically adapts to real operational variables through pheromone-based local and global updates, improving the solution iteratively with each cycle. Implications: This research provides a practical and intelligent decision-support framework for logistics planning, demonstrating that metaheuristic algorithms such as ACO can robustly handle complex delivery challenges and be scaled to broader logistics applications
Highlights:
Improves route efficiency using ACO in real delivery operations.
Reduces distance, fuel usage, and delivery time significantly.
Provides a scalable model for intelligent logistics planning.
Keywords: Ant Colony Optimization, Vehicle Routing Problem, Logistics Efficiency, Route Optimization, Metaheuristic Algorithm
B. Covaci, R. Brejea, and M. Covaci, “The Dynamic of Commerce and Logistic 4.0: Evidences from the European and Romanian,” Annals of the Academy of Romanian Scientists Series on Agriculture, Silviculture and Veterinary Medicine Sciences, vol. 11, no. 1, pp. 62–71, 2022.
M. Tohir, A. Primadi, and S. P. Akmalia, “Analisis Infrastruktur, Distribusi dan Warehousing terhadap Sistem Logistik di Indonesia,” Jurnal Manajemen dan Pemasaran Digital, vol. 1, no. 2, pp. 101–109, 2023. [Online]. Available: https://siberpublisher.org/https://creativecommons.org/licenses/by/4.0/
B. K. Simpony, S. I. P. Rizaldy, S. Suleman, and P. Widodo, “Sistem Informasi Logistik Menggunakan Metode Prototype,” Jurnal Khatulistiwa Informatika, vol. 10, no. 2, pp. 90–98, 2022, doi: 10.31294/jki.v10i2.14093.
Y. R. Akbar and Mar’aini, “Optimasi Produksi pada Industri Kecil dan Menengah Karya Unisi dengan Penerapan Model Linear Programming,” JIP: Jurnal Inovasi Penelitian, vol. 2, no. 8, pp. 2883–2892, 2022.
A. F. Sidabutar and R. Habibi, Sistem Optimasi Penjadwalan dan Biaya Transportasi Pengiriman Barang. Buku Pedia, 2022.
S. Sahara and Y. Saputra, “Pengaruh Transportasi Darat terhadap Kelancaran Distribusi Logistik,” Innovation: Journal of Social Science Research, vol. 3, no. 6, pp. 8794–8800, 2023.
A. Styawati, A. Nurkholis, Z. Abidin, and H. Sulistiani, “Optimasi Parameter Support Vector Machine Berbasis Algoritma Firefly pada Data Opini Film,” JRESTI: Jurnal Rekayasa Sistem dan Teknologi Informasi, vol. 5, no. 5, pp. 904–910, 2021, doi: 10.29207/resti.v5i5.3380.
N. F. Lakutu, M. R. Katili, S. L. Mahmud, and N. I. Yahya, “Algoritma Dijkstra dan Algoritma Greedy untuk Optimasi Rute Pengiriman Barang pada Kantor Pos Gorontalo,” Euler: Jurnal Ilmiah Matematika, Sains dan Teknologi, vol. 11, no. 1, pp. 55–65, 2023, doi: 10.34312/euler.v11i1.18244.
S. S. N. Amida, Sahriyal, and L. Trisnawati, “Perencanaan Rute Pengangkutan Sampah dengan Metode Vehicle Routing Problem,” Innovation: Journal of Social Science Research, vol. 4, no. 1, pp. 4059–4072, 2024.
R. Y. C. Sianturi, B. Rahayudi, and A. W. Widodo, “Implementasi Algoritma Ant Colony Optimization untuk Optimasi Rute Distribusi Produk Kebutuhan Pokok dari Toko Sasana Bonafide Mojoroto,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 5, no. 7, pp. 3190–3197, 2021.
M. D. Khairansyah, M. L. Ashari, and I. Mufidah, “Penentuan Jalur Evakuasi Terpendek pada Industri Plastik Menggunakan Ant Colony Optimization,” Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety), vol. 8, no. 1, pp. 53–61, 2021, doi: 10.46447/ktj.v8i1.312.
S. D. R. Ramadhani, H. A. Tanggono, and R. Yusuf, “Optimasi Rute Distribusi Menggunakan Metode Tabu Search pada Perusahaan Daerah Air Minum (PDAM) Tirta Bangun Kulon Progo,” Proceeding Series of Physics and Formal Sciences, vol. 1, pp. 56–60, 2021, doi: 10.30595/pspfs.v1i.134.
M. K. P. Santoso, H. A. Kurlillah, Purwanti, A. T. Anggita, N. S. B. Nk, and N. A. D. Prahesti, “Penentuan Rute Distribusi LPG Menggunakan Teknik Simulated Annealing pada PT XYZ,” Jurnal Penelitian Rumpun Ilmu Teknik, vol. 3, no. 4, pp. 68–76, 2024.
A. Mufliq, A. K. Alhaq, and R. A. Nugroho, “Optimasi Rute Distribusi Bantuan Sosial di Kabupaten Pacitan Menggunakan Algoritma Particle Swarm Optimization,” Ilkom: Jurnal Computer Science and Applications Informatics, vol. 6, no. 3, pp. 252–259, 2024.
D. A. F. Anggraeni, V. R. Dianutami, and R. Tyasnurita, “Investigation of Simulated Annealing and Ant Colony Optimization to Solve Delivery Routing Problem in Surabaya, Indonesia,” Procedia Computer Science, vol. 234, pp. 592–601, 2024, doi: 10.1016/j.procs.2024.03.044.