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Modelling and solving the multiperiod inventory-routing problem with stochastic stationary demand rates

Abdul Rahim, Mohd Kamarul Irwan and Zhong, Yiqing and Aghezzaf, El-Houssaine and Aouam, Tarik (2014) Modelling and solving the multiperiod inventory-routing problem with stochastic stationary demand rates. International Journal of Production Research, 52 (14). pp. 4351-4363. ISSN 0020-7543

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Abstract

The inventory-routing problem (IRP) is a typical logistics optimisation problem that supply chains, implementing vendor managed inventory (VMI), are confronted with.It combines inventory control and vehicle routing.The main objective of the IRP is to jointly determine optimal quantities of the product to be delivered to the retailers, delivery periods and optimal vehicle routes for the shipment of these quantities.This paper considers a multiperiod inventory-routing problem with stochastic stationary demand rates (MP-SIRP).The problem is first formulated as a linear mixed-integer stochastic program for which we propose a deterministic equivalent approximation model (MP-DAIRP).This latter model can be decomposed into two well-know subproblems: an inventory allocation subproblem and a vehicle routing subproblem. The stochastic aspect of the demand is accounted for in the inventory allocation subproblem.The vehicle routing subproblem is solved as a deterministic mixed-integer problem.Lagrangian relaxation is used to determine close to optimal feasible solutions for the MP-DAIRP.Results of the proposed Lagrangian relaxation approach on some numerical examples are reported and thoroughly discussed.

Item Type: Article
Uncontrolled Keywords: multiperiod inventory routing, stochastic demand rate, mixed-integer programming, Lagrangian relaxation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Technology Management & Logistics
Depositing User: Dr. Mohd Kamarul Irwan Abdul Rahim
Date Deposited: 08 Mar 2016 07:14
Last Modified: 27 Apr 2016 02:25
URI: https://repo.uum.edu.my/id/eprint/17446

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