Vol 19, No 2 (2021)

Penentuan Rute Pengiriman Beras Menggunakan Metode Nearest Neighbour dan Mixed Integer Linear Programming

Cahyono Sigit Pramudyo, Hafiztha Aryunda Tanggono, Muh. Hasyim Asy'ari

Abstract


Distribusi produk berperan penting dalam kinerja rantai pasok. Proses pendistribusian barang seringkali hanya mengandalkan intuisi pengemudi kendaraan. Hal ini berarti urutan pengiriman ditentukan secara acak menurut kehendak pengemudi. Akibatnya, pengiriman barang menempuh rute yang tidak optimal. Rute yang tidak optimal ini berarti pemborosan bagi kinerja rantai pasok. Untuk mengatasi masalah ini, makalah ini menggunakan kombinasi dua metode untuk menentukan rute pengiriman beras yang meminimumkan total jarak tempuh. Metode pertama yang digunakan termasuk kategori Metode Heuristic  yaitu Nearest Neighbour. Metode kedua berkategori metode optimasi, yaitu Metode Mixed Integer Linear Programming. Kombinasi dua metode tersebut diimplementasikan pada masalah pengiriman barang berupa beras Bantuan Pangan Non Tunai (BPNT) yang dilakukan oleh BULOG di wilayah Kota Yogyakarta. Data yang digunakan pada penelitian ini adalah data jarak antar gudang menuju Rumah Pangan Kita (RPK) dan jarak antar RPK serta data permintaan tiap RPK. Pertama, data diolah menggunakan metode nearest neighbour. Hasil tahap pertama disebut solusi awal. Selanjutnya, solusi awal diolah menggunakan Metode Mixed Integer Linear Programming. Solusi rute menggunakan metode nearest neighbour menurunkan jarak sebesar 14,98%. Pengolahan lanjutan menggunakan Metode Mixed Integer Linear Programming menambah penurunan jarak sebesar 1,45 %.


Keywords


Optimasi; Distribusi; Rantai Pasok; Mixed integer linear programming.

References


Berhan, Eshetie, Birhanu Beshah, Daniel Kitaw, and Ajith Abraham. 2014. “Stochastic Vehicle Routing Problem: A Literature Survey.” Journal of Information and Knowledge Management 13 (3). https://doi.org/10.1142/S0219649214500221.

Bruglieri, M., S. Mancini, and O. Pisacane. 2019. “The Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations.” Computers and Operations Research 112. https://doi.org/10.1016/j.cor.2019.07.017.

Chen, Lijian, Wen Chyuan Chiang, Robert Russell, Jun Chen, and Dengfeng Sun. 2018. “The Probabilistic Vehicle Routing Problem with Service Guarantees.” Transportation Research Part E: Logistics and Transportation Review 111 (January): 149–64. https://doi.org/10.1016/j.tre.2018.01.012.

Domínguez-Martín, Bencomo, Inmaculada Rodríguez-Martín, and Juan José Salazar-González. 2018. “The Driver and Vehicle Routing Problem.” Computers and Operations Research 92: 56–64. https://doi.org/10.1016/j.cor.2017.12.010.

Gouveia, Luis. 1995. “A Result on Projection for the Vehicle Routing Ptoblem.” European Journal of Operational Research. https://doi.org/10.1016/0377-2217(94)00025-8.

Gutierrez, Andres, Laurence Dieulle, Nacima Labadie, and Nubia Velasco. 2018. “A Hybrid Metaheuristic Algorithm for the Vehicle Routing Problem with Stochastic Demands.” Computers and Operations Research 99: 135–47. https://doi.org/10.1016/j.cor.2018.06.012.

Helal, Nathalie, Frédéric Pichon, Daniel Porumbel, David Mercier, and Éric Lefèvre. 2018. “The Capacitated Vehicle Routing Problem with Evidential Demands.” International Journal of Approximate Reasoning 95: 124–51. https://doi.org/10.1016/j.ijar.2018.02.003.

Huang, Ying Hua, Carola A. Blazquez, Shan Huen Huang, Germán Paredes-Belmar, and Guillermo Latorre-Nuñez. 2019. “Solving the Feeder Vehicle Routing Problem Using Ant Colony Optimization.” Computers and Industrial Engineering 127 (October 2018): 520–35. https://doi.org/10.1016/j.cie.2018.10.037.

Juliandri, Dedy, Herman Mawengkang, and F. Bu’Ulolo. 2018. “Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints.” IOP Conference Series: Materials Science and Engineering 300 (1). https://doi.org/10.1088/1757-899X/300/1/012024.

Letchford, Adam N., and Juan José Salazar-González. 2019. “The Capacitated Vehicle Routing Problem: Stronger Bounds in Pseudo-Polynomial Time.” European Journal of Operational Research 272 (1): 24–31. https://doi.org/10.1016/j.ejor.2018.06.002.

Liu, Changshi, Gang Kou, Xiancheng Zhou, Yi Peng, Huyi Sheng, and Fawaz E. Alsaadi. 2020. “Time-Dependent Vehicle Routing Problem with Time Windows of City Logistics with a Congestion Avoidance Approach.” Knowledge-Based Systems 188: 1–13. https://doi.org/10.1016/j.knosys.2019.06.021.

Savitri, H., and D. A. Kurniawati. 2018. “Sweep Algorithm and Mixed Integer Linear Program for Vehicle Routing Problem with Time Windows.” Journal of Advanced Manufacturing Systems 17 (4): 505–13. https://doi.org/10.1142/S0219686718500282.

Shi, Jianli, Jin Zhang, Kun Wang, and Xin Fang. 2018. “Particle Swarm Optimization for Split Delivery Vehicle Routing Problem.” Asia-Pacific Journal of Operational Research 35 (2). https://doi.org/10.1142/S0217595918400067.

Wang, Yong, Kevin Assogba, Jianxin Fan, Maozeng Xu, Yong Liu, and Haizhong Wang. 2019. “Multi-Depot Green Vehicle Routing Problem with Shared Transportation Resource: Integration of Time-Dependent Speed and Piecewise Penalty Cost.” Journal of Cleaner Production 232: 12–29. https://doi.org/10.1016/j.jclepro.2019.05.344.


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DOI: 10.25104/mtm.v19i2.2034

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