VRP complex network analysis and simulation

  • Gabriel Policroniades Chípuli  ,
  • Idalia Flores de la Mota  ,
  • Javier Lara de Paz  ,
  •  d Sashiko Sihirai Reyna  
  • a,b,c,d Universidad Nacional Autónoma de México, Mexico
Cite as
Policroniades Chípuli G., Flores de la Mota I., Lara de Paz J., Shirai Reyna O. S. (2019). VRP complex network analysis and simulation. Proceedings of the 31st European Modeling & Simulation Symposium (EMSS 2019), pp. 342-351. DOI: https://doi.org/10.46354/i3m.2019.emss.048.

Abstract

When carrying out a systemic analysis of a distribution network, it is possible to identify controllable and noncontrollable factors for decision makers, when the system being disaggregated into greater levels of detail, which may affect compliance with a deterministic routing plan. Some of these factors, to mention a few, may include late deliveries of raw material, unexpected transportation failures, unexpected closures of some distribution center; among others. If this type of analysis is combined with a topological analysis of the network as complex one, then it will be possible to develop more robust networks that can deal with a greater number of adversities. Identifying the topological analysis as an opportunity niche for the elaboration of possible scenarios to improve the flow through the entire network. These scenarios have been simulated in SIMIO. One way to mix both principles, is possible to find in the method proposed by authors. A case study is shown in the automotive industry.

References

  1. Aleta, A., Meloni, S., & Moreno, Y. (2016). A multilayer perspective for the analysis of urban transportation systems. arXiv:1607.00072 [cond-mat, physics:physics]. Recuperado de http://arxiv.org/abs/1607.00072
  2. Banks, C. M. (2010). Introduction to Modeling and Simulation. En Modeling and Simulation Fundamentals (pp. 1-24). https://doi.org/10.1002/9780470590621.ch1
  3. Banks, J. (1998). Wiley: Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice - Jerry Banks. Recuperado de http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471134031.html
  4. Barceló, J., Grzybowska, H., & Pardo, S. (2007). Vehicle Routing And Scheduling Models, Simulation And City Logistics. En Operations Research/Computer Science Interfaces Series. Dynamic Fleet Management (pp. 163-195). https://doi.org/10.1007/978-0-387-71722-7_8
  5. Berhan, E., Beshah, B., Kitaw, D., & Abraham, A. (2014). Stochastic Vehicle Routing Problem: A Literature Survey. Journal of Information & Knowledge Management, 13(03), 1450022. https://doi.org/10.1142/S0219649214500221
  6. Bertsimas, D. J. (1992). A Vehicle Routing Problem with Stochastic Demand. Operations Research, 40(3), 574-585. https://doi.org/10.1287/opre.40.3.574
  7. Boccaletti, S., Bianconi, G., Criado, R., del Genio, C. I., Gómez-Gardeñes, J., Romance, M., … Zanin, M. (2014). The structure and dynamics of multilayer networks. Physics Reports, 544(1), 1-122. https://doi.org/10.1016/j.physrep.2014.07.001
  8. Braekers, K., Ramaekers, K., & Van Nieuwenhuyse, I. (2016). The vehicle routing problem: State of the art classification and review. Computers & Industrial Engineering, 99, 300-313. https://doi.org/10.1016/j.cie.2015.12.007
  9. Braese, Niklas. (2005). The Dynamics of Supply Chains in the Automotive Industry. Massachusetts Institute of Technology.
  10. Carson, Y., & Maria, A. (1997). Simulation Optimization: Methods And Applications. 118-126. Recuperado de https://www.computer.org/csdl/proceedings/wsc/1997/4278/00/42780118.pdf
  11. Cartledge, C. L., & Nelson, M. L. (2011). Connectivity Damage to a Graph by the Removal of an Edge or a Vertex. arXiv:1103.3075 [cs]. Recuperado de http://arxiv.org/abs/1103.3075
  12. Casasnovas, D. J. P. (2012). Some Basic Concepts on Complex Networks and Games. En Springer Theses. Evolutionary Games in Complex Topologies (pp. 9-46). https://doi.org/10.1007/978-3-642-30117-9_2
  13. Cordeau, J.-F., Laporte, G., Savelsbergh, M. W. P., & Vigo, D. (2007). Chapter 6 Vehicle Routing. En C. B. and G. Laporte (Ed.), Handbooks in Operations Research and Management Science (pp. 367-428). https://doi.org/10.1016/S0927-0507(06)14006-2
  14. Estrada, E. (2015). Introduction to Complex Networks: Structure and Dynamics. En J. Banasiak & M. Mokhtar-Kharroubi (Eds.), Evolutionary Equations with Applications in Natural Sciences (pp. 93-131). https://doi.org/10.1007/978-3-319-11322-7_3
  15. Fan, W., Xu, H., & Xu, X. (2009). Simulation on vehicle routing problems in logistics distribution. COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, 28(6), 1516-1531. https://doi.org/10.1108/03321640910992056
  16. Gallotti, R., Porter, M. A., & Barthelemy, M. (2016). Lost in transportation: Information measures and cognitive limits in multilayer navigation. Science Advances, 2(2), e1500445. https://doi.org/10.1126/sciadv.1500445
  17. Holme, P., Kim, B. J., Yoon, C. N., & Han, S. K. (2002). Attack vulnerability of complex networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 65(5 Pt 2), 056109. https://doi.org/10.1103/PhysRevE.65.056109
  18. Huang, K., Wu, K.-F., & Ardiansyah, M. N. (2018). A stochastic dairy transportation problem considering collection and delivery phases. Transportation Research Part E: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2018.01.018
  19. Juan, A. A., Faulin, J., Pérez-Bernabeu, E., & Domínguez, O. (2013). Simulation-Optimization Methods in Vehicle Routing Problems: A Literature Review and an Example. En Lecture Notes in Business Information Processing. Modeling and Simulation in Engineering, Economics, and Management (pp. 115-124). https://doi.org/10.1007/978-3-642-38279-6_13
  20. Lei, W., Mingfang, G., & Lijun, W. (2012). The Directed Complex Network Application in the Supply Chain. 2012 Third International Conference on Digital Manufacturing Automation, 911-914. https://doi.org/10.1109/ICDMA.2012.215
  21. Mohammed, M. A., Ghani, M. K. A., Hamed, R. I., Mostafa, S. A., Ahmad, M. S., & Ibrahim, D. A. (2017). Solving Vehicle Routing Problem by Using Improved Genetic Algorithm for Optimal Solution. Journal of Computational Science. https://doi.org/10.1016/j.jocs.2017.04.003
  22. Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008a). A survey on pickup and delivery problems. Journal Für Betriebswirtschaft, 58(2), 81-117. https://doi.org/10.1007/s11301-008-0036-4
  23. Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008b). A survey on pickup and delivery problems. Journal Für Betriebswirtschaft, 58(1), 21-51. https://doi.org/10.1007/s11301-008-0033-7
  24. Policroniades, G., & Flores de la Mota, I. (2016). State of the Art of the Different Models of Transportation Most Used in the Supply Chain of Automotive Industry. International Journal of Combinatorial Optimization Problems and Informatics, 7(3), 44-53.
  25. Policroniades, G., Flores de la Mota, I., Sihirai Reyna, O. S., & Lara de Paz, J. (2018). The Vehicle Routing Problem Complex Network Analysis. Journal of Applied Mathematics and Computation, 2(12). https://doi.org/10.26855/jamc.2018.12.001
  26. Prawda, J. (1991). Metodos y modelos de investigacion de operaciones . Vol I-II (Decima). Recuperado de https://www.iberlibro.com/Metodosmodelos-investigacion-operaciones-Vol-III/10051661077/bd
  27. Von Bertalanffy, L. (1976). TEORIA GENERAL DE LOS SISTEMAS. Recuperado de http://www.gandhi.com.mx/teoria-general-delos-sistemas