Vehicle Routing Problem Optimization for Rebar Material Distribution using the Symbiotic Organisms Search Method
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The success rate of construction projects depends on subcontractors and material suppliers, especially in ensuring the material delivery to avoid delays and cost overruns. The Vehicle Routing Problem (VRP) addresses transportation management to minimize the distribution costs. This study presents a comparative analysis of three VRP scenarios: the existing case, the Capacitated Vehicle Routing Problem (CVRP), and the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). The Symbiotic Organisms Search (SOS) method is used to solve the VRP of a building materials supplier in Sulawesi, Indonesia in delivering rebar to 19 locations over 12 weeks while considering the vehicle capacity and the time window constraints. The results show that the SOS method effectively handles the rebar distribution problems with these constraints. The CVRP scenario achieves a total cost saving of Rp 23,263,278 (26.15%), while the CVRPTW scenario saves Rp 6,732,942 (7.57%).
Wegelius-Lehtonen, T. and Pahkala, S., Developing Material Delivery Processes in Cooperation: An Application Example of The Construction Industry, International Journal of Production Economics, 56–57, 1998, pp. 689–698, doi: 10.1016/S0925-5273(98)00077-2.
Karundeng, T.N., Mandey, S.L., and Sumarauw, J.S.B., Analisis Saluran Distribusi Kayu (Studi Kasus di CV. Karya Abadi, Manado), Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis dan Akuntansi, 6(3), 2018, pp. 1748–1757, doi: 10.35794/emba.v6i3.20444.
Puspitasari, F.H. and Kurniawan, V.R.B., Designing Optimal Distribution Routes using a Vehicle Routing Problem (VRP) Model in a Logistics Service Provider, IOP Conference Series: Material Science and Engineering, 1071(1), 2021, p. 012005, doi: 10.1088/1757-899X/1071/1/012005.
Dantzig, G.B. and Ramser, J.H., The Truck Dispatching Problem, Management Science, 6(1), 1959, pp. 80–91, doi: 10.1287/mnsc.6.1.80.
Setak, M., Habibi, M., Karimi, H., and Abedzadeh, M., A Time-Dependent Vehicle Routing Problem in Multigraph with FIFO Property, Journal of Manufacturing Systems, 35, 2015, pp. 37–45, doi: 10.1016/j.jmsy.2014.11.016.
Kumar, S.N. and Panneerselvam, R., A Survey on the Vehicle Routing Problem and Its Variants, Intelligent Information Management, 4(3), 2012, pp. 66–74, doi: 10.4236/iim.2012.43010.
Marinakis, Y., Marinaki, M., and Migdalas, A., A Multi-Adaptive Particle Swarm Optimization for The Vehicle Routing Problem with Time Windows, Information Sciences, 481, 2019, pp. 311–329, doi: 10.1016/j.ins.2018.12.086.
Braekers, K., Ramaekers, K., and Van Nieuwenhuyse, I., The Vehicle Routing Problem: State of The Art Classification and Review, Computers & Industrial Engineering, 99, 2016, pp. 300–313, doi: 10.1016/j.cie.2015.12.007.
Konstantakopoulos, G.D., Gayialis, S.P., and Kechagias, E.P., Vehicle Routing Problem and Related Algorithms for Logistics Distribution: A Literature Review and Classification, Operational Research, 22(3), 2022, pp. 2033–2062, doi: 10.1007/s12351-020-00600-7.
Wang, C.H. and Lu, J.Z., A Hybrid Genetic Algorithm That Optimizes Capacitated Vehicle Routing Problems, Expert Systems with Applications, 36(2), 2009, pp. 2921–2936, doi: 10.1016/j.eswa.2008.01.072.
Khairy, O.M., Shehata, O.M., and Morgan, E.I., Meta-heuristic Algorithms for Solving The Multi-Depot Vehicle Routing Problem, 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES), IEEE, Giza, Egypt, October, 2020, pp. 276–281, doi: 10.1109/NILES50944.2020.9257879.
Bodin, L. and Golden, B., Classification in Vehicle Routing and Scheduling, Networks, 11(2), 1981, pp. 97–108, doi: 10.1002/net.3230110204.
Prayogo, D., Sutanto, J.C., Suryo, H.E., and Eric, S., A Comparative Study on Bio-Inspired Algorithms in Layout Optimization of Construction Site Facilities, Civil Engineering Dimension, 20(2), 2018, pp. 102–110, doi: 10.9744/ced.20.2.102-110.
Prayogo, D. and Kusuma, C.T., Optimization of Resource Leveling Problem Under Multiple Objective Criteria Using A Symbiotic Organisms Search, Civil Engineering Dimension, 21(1), 2019, pp. 43–51, doi: 10.9744/ced.21.1.43-49.
Budi, G.S., Chandra, J.G., Ongkowardhana, B.S., and Husada, W., Optimization of Counterfort Retaining Wall Structure with Shear Key using Metaheuristic Method, Civil Engineering Dimension, 26(2), 2024, pp. 151–159, doi: 10.9744/ced.26.2.151-159.
Ho, W., Ho, G.T.S., Ji, P., and Lau, H.C.W., A Hybrid Genetic Algorithm for The Multi-Depot Vehicle Routing Problem, Engineering Applications of Artificial Intelligence, 21(4), 2008, pp. 548–557, doi: 10.1016/j.engappai.
2007.06.001.
Khouadjia, M.R., Sarasola, B., Alba, E., Jourdan, L., and Talbi, E.G., A Comparative Study Between Dynamic Adapted PSO and VNS for The Vehicle Routing Problem with Dynamic Requests, Applied Soft Computing, 12(4), 2012, pp. 1426–1439, doi: 10.1016/j.asoc.2011.10.023.
Zhang, H., Zhang, Q., Ma, L., Zhang, Z., and Liu, Y., A Hybrid Ant Colony Optimization Algorithm for A Multi-Objective Vehicle Routing Problem with Flexible Time Windows, Information Sciences, 490, 2019, pp. 166–190, doi: 10.1016/j.ins.2019.03.070.
Cheng, M.Y. and Prayogo, D., Symbiotic Organisms Search: A New Metaheuristic Optimization Algorithm, Computers & Structures, 139, 2014, pp. 98–112, doi: 10.1016/j.compstruc.2014.03.007.
Ezugwu, A.E. and Prayogo, D., Symbiotic Organisms Search Algorithm: Theory, Recent Advances and Applications, Expert Systems with Applications, 119, 2019, pp. 184–209, doi: 10.1016/j.eswa.2018.10.045.
Gharehchopogh, F.S., Shayanfar, H., and Gholizadeh, H., A Comprehensive Survey on Symbiotic Organisms Search Algorithms, Artificial Intelligence Review, 53(3), 2020, pp. 2265–2312, doi: 10.1007/s10462-019-09733-4.
Abdullahi, M., Ngadi, M.A., Dishing, S.I., Abdulhamid, S.M., and Usman, M.J., A Survey of Symbiotic Organisms Search Algorithms and Applications, Neural Computing & Applications, 32(2), 2020, pp. 547–566, doi: 10.1007/s00521-019-04170-4.
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