Abstract
This paper deals with a facility location problem where decisions must be made in the presence of uncertainty. The studied distribution network is composed of a single supplier serving a set of retailers through a set of distribution centers (DCs) to locate on the retailer's locations. The inventory at each DC is controlled using an EOQ policy and a safety stock is kept to ensure a given retailers service level. A two-period stochastic programming model is proposed in which DCs located in the first period can fail in the second period. The goal is to minimize the total DCs location costs, transportation costs through the network, inventory and safety stock costs at the DCs. A Monte Carlo optimization approach combining the sample average approximation (SAA) scheme and an efficient Lagrangian relaxation method is proposed to solve the problem. Some computational results are presented and analysed to show the effectiveness of the proposed approach.
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