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|Title:||Combining Monte-Carlo simulation with heuristics for solving the inventory routing problem with stochastic demands|
|Author:||Cáceres Cruz, José de Jesús|
Juan Pérez, Ángel Alejandro
Grasman, Scott Erwin
Faulin Fajardo, Francisco Javier
Monte Carlo methods
|Publisher:||Winter Simulation Conference (WSC). Proceedings|
|Citation:||Cáceres-Cruz, J., Juan, A.A., Grasman, S., Bektas, T. & Faulin Fajardo, F.J. (2012). Combining Monte-Carlo Simulation with Heuristics for solving the Inventory Routing Problem with Stochastic Demands. Winter Simulation Conference (WSC). Proceedings, 2012(), 3114-3122. doi: 10.1109/WSC.2012.6464999|
|Published in:||Winter Simulation Conference, Berlín, Alemanya, 9-12, desembre de 2012|
|Abstract:||In this paper, we introduce a simulation-based algorithm for solving the single-period Inventory Routing Problem (IRP) with stochastic demands. Our approach, which combines simulation with heuristics, considers different potential inventory policies for each customer, computes their associated inventory costs according to the expected demand in the period, and then estimates the marginal routing savings associated with each customer-policy entity. That way, for each customer it is possible to rank each inventory policy by estimating its total costs, i.e., both inventory and routing costs. Finally, a multi-start process is used to iteratively construct a set of promising solutions for the IRP. At each iteration of this multi-start process, a new set of policies is selected by performing an asymmetric randomization on the list of policy ranks. Some numerical experiments illustrate the potential of our approach.|
|Appears in Collections:||Articles|
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