Abstract
We study an extension of the delivery dispatching problem (DDP) with time windows, applied on LTL orders arriving at an urban consolidation center. Order properties (e.g., destination, size, dispatch window) may be highly varying, and directly distributing an incoming order batch may yield high costs. Instead, the hub operator may wait to consolidate with future arrivals. A consolidation policy is required to decide which orders to ship and which orders to hold. We model the dispatching problem as a Markov decision problem. Dynamic Programming (DP) is applied to solve toy-sized instances to optimality. For larger instances, we propose an Approximate Dynamic Programming (ADP) approach. Through numerical experiments, we show that ADP closely approximates the optimal values for small instances, and outperforms two myopic benchmark policies for larger instances. We contribute to literature by (i) formulating a DDP with dispatch windows and (ii) proposing an approach to solve this DDP.
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Bookbinder, J.H., Cai, Q., He, Q.M.: Shipment consolidation by private carrier: the discrete time and discrete quantity case. Stochastic Models 27(4), 664–686 (2011)
Coelho, L.C., Laporte, G., Cordeau, J.F.: Dynamic and stochastic inventory-routing. Technical Report CIRRELT 2012–37, CIRRELT (2012)
Coelho, L.C., Cordeau, J.F., Laporte, G.: Thirty years of inventory routing. Transportation Science 48(1), 1–19 (2014)
Daganzo, C.F.: The distance traveled to visit n points with a maximum of c stops per vehicle: An analytic model and an application. Transportation Science 18(4), 331–350 (1984)
Lium, A.G., Crainic, T.G., Wallace, S.W.: A study of demand stochasticity in service network design. Transportation Science 43(2), 144–157 (2009)
Minkoff, A.S.: A markov decision model and decomposition heuristic for dynamic vehicle dispatching. Operations Research 41(1), 77–90 (1993)
Mutlu, F., Çetinkaya, S., Bookbinder, J.: An analytical model for computing the optimal time-and-quantity-based policy for consolidated shipments. IIE Transactions 42(5), 367–377 (2010)
Pillac, V., Gendreau, M., Guéret, C., Medaglia, A.L.: A review of dynamic vehicle routing problems. European Journal of Operational Research 225(1), 1–11 (2013)
Powell, W.B.: Approximate Dynamic Programming: Solving the Curses of Dimensionality, vol. 842. John Wiley & Sons (2011)
Powell, W.B., Topaloglu, H.: Stochastic programming in transportation and logistics. Handbooks in Operations Research and Management Science 10, 555–635 (2003)
Quak, H.: Sustainability of urban freight transport: Retail distribution and local regulations in cities. No. EPS-2008-124-LIS. Erasmus Research Institute of Management (ERIM) (2008)
Ritzinger, U., Puchinger, J., Hartl, R.F.: A survey on dynamic and stochastic vehicle routing problems. International Journal of Production Research, 1–17 (2015). (ahead-of-print)
Robusté, F., Estrada, M., López-Pita, A.: Formulas for estimating average distance traveled in vehicle routing problems in elliptic zones. Transportation Research Record: Journal of the Transportation Research Board 1873(1), 64–69 (2004)
SteadieSeifi, M., Dellaert, N., Nuijten, W., Van Woensel, T., Raoufi, R.: Multimodal freight transportation planning: A literature review. European Journal of Operational Research 233(1), 1–15 (2014)
Topaloglu, H., Powell, W.B.: Dynamic-programming approximations for stochastic time-staged integer multicommodity-flow problems. INFORMS Journal on Computing 18(1), 31–42 (2006)
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van Heeswijk, W., Mes, M., Schutten, M. (2015). An Approximate Dynamic Programming Approach to Urban Freight Distribution with Batch Arrivals. In: Corman, F., Voß, S., Negenborn, R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science(), vol 9335. Springer, Cham. https://doi.org/10.1007/978-3-319-24264-4_5
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DOI: https://doi.org/10.1007/978-3-319-24264-4_5
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