Determination of the Medical Equipment Delivery Route for PT Tri Sapta Jaya Using Simulated Annealing (SA) Algorithm
DOI:
https://doi.org/10.59653/ijmars.v2i01.405Keywords:
Capacity Vehicle Routing Problem, Simulated Annealing, Delivery, Medical DistributorAbstract
This research was conducted at PT Tri Sapta Jaya, a medical equipment distributor company. The product distribution to consumers was inefficient due to using traditional methods. The division of regions and determination of delivery routes was based on districts and cities. The existing delivery method faced various challenges, including delivery delays and inefficient routes. This inefficiency results in potential financial losses for the company in terms of delivery costs. To assist the company in improving delivery efficiency, this research focuses on determining vehicle routes considering vehicle capacity (Capacity Vehicle Routing Problem). In solving and searching for solutions, the research uses Simulated-Annealing algorithm. The algorithm generated an initial solution randomly and improved the solution by changing the positions of consumers within a route and switching positions of consumers between routes to obtain the best solution. The computation time of the developed Simulated Annealing algorithm was quite efficient, taking only 2 seconds for 25 consumers. Based on the data from PT Tri Sapta Jaya, the best solution obtained was 615,319. This result was achieved using the Simulated Annealing algorithm with the parameters T0 = 100,000, Ta = 1, and α = 0.9.
Downloads
References
Abdel-Basset, M., Abdel-Fatah, L., & Sangaiah, A. K. (2018). Metaheuristic algorithms: A comprehensive review. In Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications. Elsevier Inc. https://doi.org/10.1016/B978-0-12-813314-9.00010-4
Andriansyah, Novatama, R., & Denny Sentia, P. (2020). Simulated Annealing Algorithm for Heterogeneous Vehicle Routing Problem (Case Study). Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 7(5). https://doi.org/10.25126/jtiik.202072018
Archetti, C., Fernández, E., & Huerta-Muñoz, D. L. (2017). The Flexible Periodic Vehicle Routing Problem. In Computers and Operations Research (Vol. 85). https://doi.org/10.1016/j.cor.2017.03.008
Aydemir, E., & Karagul, K. (2020). Solving a Periodic Capacitated Vehicle Routing Problem using Simulated Annealing Algorithm for a Manufacturing Company. Brazilian Journal of Operations & Production Management, 17(1), 1–13. https://doi.org/10.14488/bjopm.2020.011
Bianchessi, N., Drexl, M., & Irnich, S. (2019). The split delivery vehicle routing problem with time windows and customer inconvenience constraints. Transportation Science, 53(4), 1067–1084. https://doi.org/10.1287/trsc.2018.0862
Dassisti, M., Eslami, Y., & Mohaghegh, M. (2017). Raw material flow optimization as a capacitated vehicle routing problem: A visual benchmarking approach for sustainable manufacturing. Proceedings - 2017 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2017, 2017-Janua, 168–174. https://doi.org/10.1109/SOLI.2017.8120989
Gendreau, M., Jabali, O., & Rei, W. (2016). Future research directions in stochastic vehicle routing. Transportation Science, 50(4), 1163–1173.
Guiffrida, A. L., & Nagi, R. (2006). Cost characterizations of supply chain delivery performance. International Journal of Production Economics, 102(1), 22–36. https://doi.org/10.1016/j.ijpe.2005.01.015
İlhan, İ. (2021). An improved simulated annealing algorithm with crossover operator for capacitated vehicle routing problem. Swarm and Evolutionary Computation, 64(May 2020), 100911. https://doi.org/10.1016/j.swevo.2021.100911
Lalla-Ruiz, E., & Voß, S. (2020). A POPMUSIC approach for the Multi-Depot Cumulative Capacitated Vehicle Routing Problem. Optimization Letters, 14(3), 671–691. https://doi.org/10.1007/s11590-018-1376-1
Martens, K., Golub, A., & Robinson, G. (2012). A justice-theoretic approach to the distribution of transportation benefits: Implications for transportation planning practice in the United States. Transportation Research Part A: Policy and Practice, 46(4), 684–695. https://doi.org/10.1016/j.tra.2012.01.004
Meier, H., Lagemann, H., Morlock, F., & Rathmann, C. (2013). Key performance indicators for assessing the planning and delivery of industrial services. Procedia CIRP, 11, 99–104. https://doi.org/10.1016/j.procir.2013.07.056
Mutar, M. L., Burhanuddin, M. A., Hameed, A. S., Yusof, N., & Mutashar, H. J. (2020). An efficient improvement of ant colony system algorithm for handling capacity vehicle routing problem. International Journal of Industrial Engineering Computations, 11(4). https://doi.org/10.5267/j.ijiec.2020.4.006
Normasari, N. M. E., Yu, V. F., Bachtiyar, C., & Sukoyo. (2019). A simulated annealing heuristic for the capacitated green vehicle routing problem. Mathematical Problems in Engineering, 2019. https://doi.org/10.1155/2019/2358258
Redi, A. A. N. P., Maula, F. R., Kumari, F., Syaveyenda, N. U., Ruswandi, N., Khasanah, A. U., & Kurniawan, A. C. (2020). Simulated annealing algorithm for solving the capacitated vehicle routing problem: a case study of pharmaceutical distribution. Jurnal Sistem Dan Manajemen Industri, 4(1), 41–49. https://doi.org/10.30656/jsmi.v4i1.2215
Rizal, M. A., & Saidatuningtyas, I. (2021). Model of Flexible Periodic Vehicle Routing Problem-Service Choice Considering Inventory Status. Jurnal Teknik Industri, 22(1), 125–137. https://doi.org/10.22219/jtiumm.vol22.no1.125-137
Utama, D. M., Widjonarko, B., & Widodo, D. S. (2022). A novel hybrid jellyfish algorithm for minimizing fuel consumption capacitated vehicle routing problem. Bulletin of Electrical Engineering and Informatics, 11(3), 1272–1279. https://doi.org/10.11591/eei.v11i3.3263
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Muhammad Alde Rizal, Hendi Dwi Hardiman, Mohammad Santosa Mulyo Diningrat, Ifa Saidatuningtyas

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).