Abstract
One of the most costly operations in logistics is the distribution of goods. Inefficient vehicle routes increase distribution costs, especially for companies performing distribution operations daily. Vehicle Routing Problem (VRP) addresses this inefficiency and optimizes the distribution routes of vehicles. In this study, we developed a decision support system to solve the Vehicle Routing Problem with Time Windows and Split Delivery and applied it to a real-life case company. The data of the problem were obtained by a real logistic company, which is one of the leading Turkish logistics companies located in Izmir, Turkey. The company distributes goods to the customers located in various cities in Turkey and currently does not use any decision-making tool to optimize the routes of its trucks. We formulated the mathematical model as Mixed Integer Linear Programming (MILP) and solved it by using IBM OPL CPLEX. Our proposed decision support system clusters the customers into geographical groups and then optimizes the routes within the clusters. The results of the decision support system can be manually adjusted by the decision maker to fine-tune the routes. We demonstrated the efficiency of our proposed methodology on the regional distribution of the company. The results of the study showed that our proposed model decreases the total distribution distance by 16% and total distribution time by approximately 13%.
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References
Hillier, S.F., Lieberman, J.G.: Introduction to Operations Research, 7th edn. McGraw-Hill International Editions, New York (1995)
Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manage. Sci. 6, 80–91 (1959)
Belachgar, K.: Vehicle Routing Problem with Distance Constraints and Clustering. Al Akhawayn University, Morocco (2017)
Wen, M.: Rich vehicle routing problems and applications. Ph.D. Thesis, Technical University of Denmark, Denmark (2010)
ORION Backgrounder (2018). https://www.pressroom.ups.com/pressroom/ContentDetailsViewer.page?ConceptType=Factsheets&id=1426321616277-282
Karagul, K., Gungor, I.: A case study of heterogeneous fleet vehicle routing problem: touristic distribution application in Alanya. Int. J. Optim. Control: Theor. Appl. (IJOCTA) 4(2), 67–76 (2014)
Ceschia, S., DiGaspero, L., Schaerf, A.: Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs. J. Sched. 14, 601–615 (2011)
Kritikos, M.N., Ioannou, G.: The heterogeneous fleet vehicle routing problem with overloads and time windows. Int. J. Prod. Econ. 144(1), 68–75 (2013)
Belmecheri, F., Prins, C., Yalaoui, F., Amodeo, L.: Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows. J. Intell. Manuf. 24, 775–789 (2013)
Salhi, S., Wassan, N., Hajarat, M.: The fleet size and mix vehicle routing problem with backhauls: Formulation and set partitioning-based heuristics. Transp. Res. Part E: Logist. Transp. Rev. 56, 22–35 (2013)
Pasha, U., Hoff, A., Hvattum, L.M.: The multi-period fleet size and mix vehicle routing problem with stochastic demands. In: European Congress on Computational Methods in Applied Sciences and Engineering, pp. 121–146. Springer, Cham, May 2015
Maheo, A., Urli, T., Kilby, P.: Fleet size and mix split-delivery vehicle routing. arXiv preprint arXiv:1612.01691 (2016)
Belfiore, P., Yoshizaki, H.T.: Heuristic methods for the fleet size and mix vehicle routing problem with time windows and split deliveries. Comput. Ind. Eng. 64(2), 589–601 (1974)
Bertoli, F., Kilby, P., Urli, T.: Vehicle routing problems with deliveries split over days. J. Veh. Routing Algorithms 1, 1–17 (2018)
Chu, J.C., Yan, S., Huang, H.J.: A multi-trip split-delivery vehicle routing problem with time windows for inventory replenishment under stochastic travel times. Netw. Spatial Econ. 17, 41–68 (2017)
Bae, H., Moon, I.: Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles. Appl. Math. Model. 40(13–14), 6536–6549 (2016)
Laporte, G.: The vehicle routing problem: An overview of exact and approximate algorithms. Eur. J. Oper. Res. 59(3), 345–358 (1992)
Amini, S., Javanshir, H., Tavakkoli-Moghaddam, R.: A PSO approach for solving VRPTW with real case study. Int. J. Recent Res. Appl. Stud. 4, 118–126 (2010)
Onut, S., Kamber, M.R., Altay, G.: A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: a case study. J. Phys.: Conf. Ser. 490(1). IOP Publishing (2014)
Panapinun, K., Charnsethikul, P.: Vehicle Routing and Scheduling Problems: A Case Study of Food Distribution in Greater Bangkok. Kasetsart University, Bangkok (2005)
Worwa, K.: A case study in school transportation logistics. Res. Logistics Prod. 4(1), 45–54 (2014)
Huang, Z.: Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Min. Knowl. Discov. 2(3), 283–304 (1998)
Acknowledgment
Burak Can Özaslan, Nazmihan Öterbülbül and Emre Can Kayadelen also helped this study during their senior design project at Yasar University in 2019.
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Doğan, A., Bilici, İ., Demiral, O.K., Erdoğan, M.S., Kabadurmuş, Ö. (2020). Building a Decision Support System for Vehicle Routing Problem: A Real-Life Case Study from Turkey. In: Durakbasa, N., Gençyılmaz, M. (eds) Proceedings of the International Symposium for Production Research 2019. ISPR ISPR 2019 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31343-2_57
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