Optimasi Open Location Routing Problem Menggunakan Metode Metaheuristik Simulated Annealing, Large Neighborhood Search, dan Adaptive Large Neighborhood Search
(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(4) Universitas Gadjah Mada
(5)
(*) Corresponding Author
Abstract
Penelitian ini menyelesaikan permasalahan Open-Location Routing Problem (OLRP) yang merupakan variasi dari permasalahan Capacitated-Location Routing Problem (CLRP). OLRP ini berkembang dan menjadi relevan seiring dengan meningkatnya penggunaan jasa perusahaan logistik pihak ketiga. Perbedaan utama OLRP dengan CLRP adalah kendaraan tidak kembali ke pusat distribusi setelah melayani pelanggan dalam OLRP. OLRP dikembangkan dengan tujuan utama untuk mengurangi total biaya yang terdiri atas biaya operasional fasilitas, biaya tetap kendaraan, dan biaya perjalanan. Dalam penelitian ini dilakukan pengembangan dan perbandingan beberapa pendekatan metaheuristik berbasis Simulated Annealing (SA), Large Neighborhood Search (LNS), dan Adaptive Large Neighborhood Search (ALNS) untuk menyelesaikan OLRP. Model yang diuji memiliki 21 pelanggan dan 5 depot potensial. Hasil pengujian menunjukkan bahwa ketiga metode menyelesaikan OLRP dengan waktu komputasi dan hasil total biaya yang bervariasi. Simulated annealing menghasilkan total biaya yang minimal sebesar $321,0406 dengan waktu komputasi hanya 54 detik.
Full Text:
PDF (Indonesian)References
S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, “Optimization by Simulated Annealing,” Science, vol. 220, no. 4598, pp. 671–680, May 1983, doi: https://doi.org/10.1126/science.220.4598.671.
H. Bayram and R. ?ahin, “A New Simulated Annealing Approach for Travelling Salesman Problem,” Mathematical and Computational Applications, vol. 18, no. 3, pp. 313–322, Dec. 2013, doi: https://doi.org/10.3390/mca18030313.
R. Hanafi and E. Kozan, “A hybrid constructive heuristic and simulated annealing for railway crew scheduling,” Computers & Industrial Engineering, vol. 70, pp. 11–19, Apr. 2014, doi: https://doi.org/10.1016/j.cie.2014.01.002.
N. Moradi and Sh. Shadrokh, “A simulated annealing optimization algorithm for equal and un-equal area construction site layout problem,” DOAJ (DOAJ: Directory of Open Access Journals), Jun. 2019, doi: https://doi.org/10.22105/riej.2019.169867.1073.
Nur, V. F. Yu, C. Bachtiyar, and Sukoyo, “A Simulated Annealing Heuristic for the Capacitated Green Vehicle Routing Problem,” Mathematical Problems in Engineering, vol. 2019, pp. 1–18, Jan. 2019, doi: https://doi.org/10.1155/2019/2358258.
D. Pisinger and S. Ropke, “Large neighborhood search,” in Handbook of Metaheuristics, pp. 99–127.
S. T. Windras Mara, R. Norcahyo, P. Jodiawan, L. Lusiantoro, and A. P. Rifai, “A survey of adaptive large neighborhood search algorithms and applications,” Computers & Operations Research, vol. 146, p. 105903, Oct. 2022, doi: https://doi.org/10.1016/j.cor.2022.105903.
Jean-Baptiste Mairy, P. Schaus, and Y. Deville, “Generic adaptive heuristics for large neighborhood search,” Principles and Practice of Constraint Programming, Jan. 2010.
A. Rifai, Huu Phuc Nguyen, and Siti Zawiah Md Dawal, “Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling,” Applied Soft Computing, vol. 40, pp. 42–57, Mar. 2016, doi: https://doi.org/10.1016/j.asoc.2015.11.034.
Rachmadi Norcahyo, Achmad Pratama Rifai, Muslim Mahardika, Gesang Nugroho, and Bobby, “Minimization of hole entry and exit surface delamination on carbon fiber reinforced polymer (CFRP) drilling process using BPNN-ALNS,” AIP conference proceedings, Jan. 2024, doi: https://doi.org/10.1063/5.0179672.
Fadhil Wina Ramadhani, Wangi Pandan Sari, and Achmad Pratama Rifai, “Multi-Vehicle Capacitated Vehicle Routing Problem For Rice Commodities In Indonesia Considering The Factors Of Weather-Induced Damages And Carbon Emissions,” ASEAN Engineering Journal, vol. 14, no. 2, pp. 195–207, May 2024, doi: https://doi.org/10.11113/aej.v14.21096.
Achmad Pratama Rifai, Edi Sutoyo, Mara, and Siti Zawiah Md Dawal, “Multiobjective Sequence-Dependent Job Sequencing and Tool Switching Problem,” IEEE Systems Journal, vol. 17, no. 1, pp. 1395–1406, Mar. 2023, doi: https://doi.org/10.1109/jsyst.2022.3213767.
A. P. Rifai, S. T. Windras Mara, and R. Norcahyo, “A two-stage heuristic for the sequence-dependent job sequencing and tool switching problem,” Computers & Industrial Engineering, vol. 163, p. 107813, Jan. 2022, doi: https://doi.org/10.1016/j.cie.2021.107813.
V. F. Yu and S.-W. Lin, “A simulated annealing heuristic for the open location-routing problem,” Computers & Operations Research, vol. 62, pp. 184–196, Oct. 2015, doi: https://doi.org/10.1016/j.cor.2014.10.009.
DOI: http://dx.doi.org/10.30998/joti.v7i1.24873
Refbacks
- There are currently no refbacks.
Indexed in:
