Abstract
In logistic delivery chains time windows are common. An arrival has to be in a certain time interval, at the expense of waiting time or penalties if the time limits are exceeded. This paper looks at the optimal placement of those time intervals in a specific case of a barge visiting two ports in sequence. For the second port a possible delay or penalty should be incorporated. Next, recognising these penalty structures in data is analysed to if see certain patterns in public travel data indicate that a certain dependency exists.
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References
Agatz, N., Campbell, A., Fleischmann, M., Savelsbergh, M.: Time slot management in attended home delivery. Transportation Science 45(3), 435–449 (2011)
Agra, A., Christiansen, M., Figueiredo, R., Hvattum, L.M., Poss, M., Requejo, C.: The robust vehicle routing problem with time windows. Computers & Operations Research 40(3), 856–866 (2013)
de Armas, J., Melián-Batista, B., Moreno-Pérez, J.A., Brito, J.: GVNS for a real-world rich vehicle routing problem with time windows. Engineering Applications of Artificial Intelligence 42, 45–56 (2015)
Batsyn, M., Kalyagin, V.: An analytical expression for the distribution of the sum of random variables with a mixed uniform density and mass function. In: Models, Algorithms, and Technologies for Network Analysis, pp. 51–63. Springer (2013)
Bushuev, M.A., Guiffrida, A.L.: Optimal position of supply chain delivery window: Concepts and general conditions. International Journal of Production Economics 137(2), 226–234 (2012)
Garg, D., Narahari, Y., Viswanadham, N.: Achieving sharp deliveries in supply chains through variance pool allocation. European Journal of Operational Research 171(1), 227–254 (2006)
Guiffrida, A.L., Nagi, R.: Cost characterizations of supply chain delivery performance. International Journal of Production Economics 102(1), 22–36 (2006)
Hernandez, F., Gendreau, M., Potvin, J.Y.: Heuristics for tactical time slot management: a periodic vehicle routing problem view. International Transactions in Operational Research (2017)
Safaei, M., Issa, S., Seifert, M., Thoben, K.D., Lang, W.: A method to estimate the accumulated delivery time uncertainty in supply networks. In: Dynamics in Logistics, pp. 337–347. Springer (2013)
Safaei, M., Mehrsai, A., Thoben, K.D.: A computational method in analyzing of delivery time uncertainty for highly complex supply networks. Measurement 55, 549–563 (2014)
Salani, M., Battarra, M., Gambardella, L.M.: Exact algorithms for the vehicle routing problem with soft time windows. In: Operations Research Proceedings 2014, pp. 481–486. Springer (2016)
Tanai, Y., Guiffrida, A.L.: Reducing the cost of untimely supply chain delivery performance for asymmetric laplace distributed delivery. Applied Mathematical Modelling 39(13), 3758–3770 (2015)
Vanany, I., Zailani, S., Pujawan, N.: Supply chain risk management: literature review and future research, pp. 16–33. IGI Global (2009)
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Phillipson, F., del Vecchyo, M.O., van Ginkel, B., Huizing, D., Sangers, A. (2017). Optimising and Recognising 2-Stage Delivery Chains with Time Windows. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds) Computational Logistics. ICCL 2017. Lecture Notes in Computer Science(), vol 10572. Springer, Cham. https://doi.org/10.1007/978-3-319-68496-3_25
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DOI: https://doi.org/10.1007/978-3-319-68496-3_25
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