Optimasi Jalur Distribusi Menggunakan Pendekatan Algoritma Genetika

Arie Saputra, Desi Fadhilah

Abstract


Management and planning of transportation distribution channels are important in increasing the company's operational efficiency. Optimal distribution arrangements can reduce transportation costs and time, as well as increase product competitiveness in the market. One method used to determine the best distribution route is the Traveling Salesman Problem (TSP), which helps companies achieve maximum efficiency. This research was carried out at the AMDK CV company. Tirta Naga Lestari (TNL) as a case study to analyze product distribution to 11 locations in Aceh. Unplanned product distribution causes high shipping costs. A genetic algorithm (GA) approach is used to find the optimal distribution route. Previous research shows that GA effectively solves complex transportation problems, such as Vehicle Routing Problems (VRP) and transportation scheduling.  This research is a development of the use of the GA method for multiple routing case studies where a route repetition process occurs. This is interesting because previous studies only focused on developing GA methods for single or multiple routing cases but there was no route repetition process (looping). This research aims to determine the optimal distribution path for cases with multiple routing and repetition of the same route.  The different constraints of the solved cases require a more adaptive GA approach. From the results obtained, it is proven that it can minimize total distribution costs of IDR 2,900,000,- with an efficiency of 37.52%. This study is proven to be able to use the GA approach to solve multiple routing problems with route repetition, thus helping to find optimal route solutions that are more efficient for product distribution.


Keywords


Distribution Optimization; Vehicle Routing Problem; Genetic Algorithm

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References


E. H. Houssein, M. R. Saad, F. A. Hashim, H. Shaban, and M. Hassaballah, “Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems,” Eng. Appl. Artif. Intell., vol. 94, p. 103731, Sep. 2020, doi: 10.1016/J.ENGAPPAI.2020.103731.

Y. Zhang, “Logistics distribution scheduling model of supply chain based on genetic algorithm,” J. Ind. Prod. Eng., vol. 39, no. 2, pp. 83–88, Feb. 2022, doi: 10.1080/21681015.2021.1958938.

F. Goodarzian, H. Hosseini-Nasab, J. Muñuzuri, and M. B. Fakhrzad, “A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: A comparison of meta-heuristics,” Appl. Soft Comput., vol. 92, p. 106331, Jul. 2020, doi: 10.1016/J.ASOC.2020.106331.

Z. Zhang, Z. Zhang, X. Wang, and W. Zhu, “Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum,” Proc. AAAI Conf. Artif. Intell., vol. 36, no. 8, pp. 9136–9144, Jun. 2022, doi: 10.1609/AAAI.V36I8.20899.

M. Mahrach, G. Miranda, C. León, and E. Segredo, “Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem,” Math. 2020, Vol. 8, Page 2018, vol. 8, no. 11, p. 2018, Nov. 2020, doi: 10.3390/MATH8112018.

E. S. Sulistyono, “Model Rute Perjalanan Minimal Dengan Menggunakan Vehicle Routing Problem Pada PT X,” J. Teknol. Dan Sist. Inf. Bisnis, vol. 4, no. 2, pp. 293–299, Jul. 2022, doi: 10.47233/JTEKSIS.V4I2.497.

D. E. Sihombing and F. Ahyaningsih, “OPTIMALISASI RUTE DISTRIBUSI AIR MINUM DALAM KEMASAN MENGGUNAKAN ALGORITMA GENETIKA PADA PT. MUAL NATIO MAJU BERSAMA,” J. Ris. RUMPUN ILMU Pendidik., vol. 2, no. 1, pp. 70–83, Jan. 2023, doi: 10.55606/JURRIPEN.V2I1.815.

17523027 Syarifah Elza Ramadhani, “Implementasi Algoritma Genetika dan Tabu Search untuk Travelling Salesman Problem,” 2020, Accessed: Oct. 19, 2024. [Online]. Available: https://dspace.uii.ac.id/handle/123456789/31464

Cahya Purnomo, Vivid Dekanawati, N. Astriawati, Sumardi, and Ganda Syahputra, “Analisis Simulasi Distribusi Logistik Menggunakan Metode Transportasi,” Saintara J. Ilm. Ilmu-Ilmu Marit., vol. 6, no. 2, pp. 84–90, 2022, doi: 10.52475/saintara.v6i2.161.

I. Maryati and H. K. Wibowo, “Optimasi penentuan rute kendaraan pada sistem distribusi barang dengan ant colony optimization 1,” vol. 2012, no. Semantik, pp. 163–168, 2012.

T. G. Bhagya, “Algortitma Genetik Pada Penjadwalan Transportasi Kapal Laut (Studi Kasus PT. Pelni),” J. Ind. Manuf. Eng., vol. 5, no. 2, pp. 81–92, 2021, doi: 10.31289/jime.v5i2.5952.

D. S. Oetomo, R. F. Ramdhani, and A. P. Abdi, “Penentuan Rute Pengiriman Produk Dengan Meminimalkan Biaya Transportasi Menggunakan Metode Saving Matrik Dan Nearest Neighbour Di Pt. Aisyah Berkah Utama,” J. Sains dan Teknol. J. Keilmuan dan Apl. Teknol. Ind., vol. 22, no. 1, p. 130, 2022, doi: 10.36275/stsp.v22i1.477.

N. A. KUSUMAWARDHANI, “Model Penentuan Ukuran Lot Gabungan Dalam Sistem Rantai Pasok Single Vendor-Multi Buyer Dengan Reactive Lateral Transshipment (Studi Kasus: Umkm Batik X Di Yogyakarta),” Nov. 2022, Accessed: Oct. 21, 2024. [Online]. Available: https://dspace.uii.ac.id/handle/123456789/42138

M. Fikry, “Pengembangan Aplikasi Klasifikasi Alat Transportasi Berdasarkan Citra Digital untuk Pencatatan Aset Studi Kasus: PT. Pulo Mas Jaya,” KALBISIANA J. Sains, Bisnis dan Teknol., vol. 9, no. 1, pp. 184–197, May 2023, Accessed: Oct. 21, 2024. [Online]. Available: http://ojs.kalbis.ac.id/index.php/kalbisiana/article/view/725

Candra Wahyu Hidayat, “The Influence Of Mix Marketing On Decisions For Use Of Online Transportation Towards Global Competition,” Int. J. Sci. Technol. Manag., vol. 2, no. 4, pp. 1154–1163, 2021, doi: 10.46729/ijstm.v2i4.253.

T. Alam, S. Qamar, A. Dixit, and M. Benaida, “Genetic Algorithm: Reviews, Implementations, and Applications,” Int. J. Eng. Pedagog., vol. 10, no. 6, pp. 57–77, Jun. 2020, doi: 10.3991/IJEP.V10I6.14567.

M. Abbasi, M. Rafiee, M. R. Khosravi, A. Jolfaei, V. G. Menon, and J. M. Koushyar, “An efficient parallel genetic algorithm solution for vehicle routing problem in cloud implementation of the intelligent transportation systems,” J. Cloud Comput., vol. 9, no. 1, pp. 1–14, Dec. 2020, doi: 10.1186/S13677-020-0157-4/TABLES/3.

S. M. Homayouni, D. B. M. M. Fontes, and J. F. Gonçalves, “A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation,” Int. Trans. Oper. Res., vol. 30, no. 2, pp. 688–716, Mar. 2023, doi: 10.1111/ITOR.12878.




DOI: https://doi.org/10.35308/jopt.v10i2.10601

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