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access icon free Simulation–optimisation framework for City Logistics: an application on multimodal last-mile delivery

City Logistics has attracted considerable interest from the operations research and logistics communities during past decades. It resulted in a broad variety of promising approaches from different fields of combinatorial optimisation. However, research on urban freight transportation is currently slowing down due to two different lacks, limiting the exploratory capacity and compromise the technology transfer to the industry. First, the majority of the instances in the literature are based on the generalisation of classical instances, often not created for urban applications, or on artificial data, i.e. data not coming from any historical or empirical datasets. Thus, the validation of models and methods becomes more difficult, being the results not directly compared with real or realistic settings. Second, even when some data sources become available, there is no standard way to mixing data gathered from different sources and, from them, generate new instances for urban applications. This study aims to overcome these issues, proposing a simulation–optimisation framework for building instances and assess operational settings. To illustrate the usefulness of the framework, the authors conduct a case study, in order to evaluate the impact of multimodal delivery options to face the demand from e-commerce, in an urban context as Turin (Italy).

References

    1. 1)
      • 18. Copenhagen Economics: ‘E-commerce and delivery’, 2013.
    2. 2)
      • 4. Kong, L., Yang, Y., Lu, J.-L., et al: ‘Evaluation of urban vehicle routing algorithms’, Int. J. Digit. Content Technol. Appl., 2012, 6, (23), pp. 790799.
    3. 3)
      • 11. Tadei, R., Perboli, G., Perfetti, F.: ‘The multi-path traveling salesman problem with stochastic travel costs’, EURO J. Transp. Logist., 2017, 6, pp. 323.
    4. 4)
      • 10. Maggioni, F., Perboli, G., Tadei, R.: ‘The multi-path traveling salesman problem with stochastic travel costs: building realistic instances for city logistics applications’, Transp. Res. Procedia, 2014, 3, pp. 528536.
    5. 5)
      • 19. FTI Consulting: ‘Intra-community cross-border parcel delivery London’, 2011.
    6. 6)
      • 5. Perboli, G., Tadei, R., Vigo, D.: ‘The two-echelon capacitated vehicle routing problem: models and math-based heuristics’, Transp. Sci., 2011, 45, (3), pp. 364380.
    7. 7)
      • 20. Taniguchi, E., Kakimoto, Y.: ‘Modelling effects of e-commerce on urban freight transport’, ch. Chapter 10, 2004, pp. 135146.
    8. 8)
      • 1. Taniguchi, E., Thompson, R.: ‘Modeling city logistics’, Trans. Res. Rec., 2002, 1790, (1), pp. 4551.
    9. 9)
      • 16. Saint-Guillain, M., Deville, Y., Solnon, C.: ‘A multistage stochastic programming approach to the dynamic and stochastic VRPTW’. 12th Int. Conf. Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2015), 2015, pp. 357374, Springer International Publishing.
    10. 10)
      • 17. Cardenas, I., Beckers, J., Vanelslander, T., et al: ‘Spatial characteristics of failed and successful e-commerce deliveries in Belgian cities’. Information Systems, Logistic and Supply Chain Conf., 2016.
    11. 11)
      • 6. Escuín, D., Millán, C., Larrodé, E.: ‘Modelization of time-dependent urban freight problems by using a multiple number of distribution centers’, Netw. Spat. Econ., 2012, 12, (3), pp. 321336.
    12. 12)
      • 21. Perboli, G., Rosano, M., Gobbato, L.: ‘Parcel delivery in urban areas: do we need new business and operational models for mixing traditional and low-emission logistics?’. Technical Report, CIRRELT 2017-02 Montréal (Canada), 2017.
    13. 13)
      • 12. van Woensel, T.: ‘DATA2MOVE initiative’, 2017. Available at https://www.data2move.nl/, accessed 08 November 2017.
    14. 14)
      • 2. Kim, G., Ong, Y.S., Heng, C.K., et al: ‘City vehicle routing problem (city VRP): a review’, IEEE Trans. Intell. Transp. Syst., 2015, 16, (4), pp. 16541666.
    15. 15)
      • 9. Bektas, T., Laporte, G.: ‘The pollution-routing problem’, Transp. Res. B, Methodol., 2011, 45, (8), pp. 12321250.
    16. 16)
      • 8. Erdogan, S., Miller-Hooks, E.: ‘A green vehicle routing problem’, Transp. Res. E, Logist. Transp. Rev., 2012, 48, (1), pp. 100114.
    17. 17)
      • 3. Vigo, D.: ‘A heuristic algorithm for the asymmetric capacitated vehicle routing problem’, Eur. J. Oper. Res., 1996, 89, (1), pp. 108126.
    18. 18)
      • 14. Hart, W.E., Watson, J.-P., Woodruff, D.L.: ‘Pyomo: modeling and solving mathematical programs in python’, Math. Program. Comput., 2011, 3, (3), pp. 219260.
    19. 19)
      • 13. Crainic, T., Perboli, G., Rosano, M.: ‘Simulation of intermodal freight transportation systems: a taxonomy’. Eur. J. Oper. Res., 2017, doi: 10.1016/j.ejor.2017.11.061.
    20. 20)
      • 15. Watson, J.-P., Woodruff, D.L., Hart, W.E.: ‘PySP: modeling and solving stochastic programs in python’, Math. Program. Comput., 2012, 4, (2), pp. 109149.
    21. 21)
      • 22. URBeLOG: ‘Project Web site’, 2015. Available at http://www.urbelog.it/, accessed 08 November 2017.
    22. 22)
      • 7. Minis, I., Mamasis, K., Zeimpekis, V.: ‘Real-time management of vehicle breakdowns in urban freight distribution’, J. Heuristics, 2012, 18, (3), pp. 375400.
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