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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
Bektas, Tolga
Faulin Fajardo, Francisco Javier
Keywords: routing
stochastic processes
heuristic algorithms
educational institutions
Monte Carlo methods
Issue Date: Dec-2012
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
Project identifier: info:eu-repo/grantAgreement/TRA2010-21644-C03
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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.
Language: English
ISBN: 9781467347815
ISSN: 1558-4305MIAR
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