Managing stochastic demand in an Inventory Routing Problem with transportation procurement

Luca Bertazzi, Adamo Bosco and Demetrio Laganà

Omega, 2015, vol. 56, issue C, 112-121

Abstract: We study an Inventory Routing Problem in which the supplier has a limited production capacity and the stochastic demand of the retailers is satisfied with procurement of transportation services. The aim is to minimize the total expected cost over a planning horizon, given by the sum of the inventory cost at the supplier, the inventory cost at the retailers, the penalty cost for stock-out at the retailers and the transportation cost. First, we show that a policy based just on the average demand can have a total expected cost infinitely worse than the one obtained by taking into account the overall probability distribution of the demand in the decision process. Therefore, we introduce a stochastic dynamic programming formulation of the problem that allows us to find an optimal policy in small size instances. Finally, we design and implement a matheuristic approach, integrating a rollout algorithm and an optimal solution of mixed-integer linear programming models, which is able to solve realistic size problem instances. Computational results allow us to provide managerial insights concerning the management of stochastic demand.

Keywords: Inventory routing problem; Stochastic demand; Transportation procurement; Dynamic programming; Matheuristic (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (19)

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DOI: 10.1016/j.omega.2014.09.010

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