Distribution network design with random demand and unreliable suppliers

This paper addresses the location problem of distribution centers (DC) in a distribution network with unreliable suppliers and random demand. A two-period model is proposed in which selected suppliers are available in the first period and can fail in the second period. The facility location/supplier reliability problem is formulated as a stochastic programming problem for minimizing total fixed facility costs, transportation costs, DC replenishment costs, DC inventory and safety stock costs. Since the problem is NP-hard nonlinear stochastic optimization problem, we propose a Monte Carlo optimization approach combining the sample average approximation (SAA) scheme and an efficient heuristic based on Lagrangian relaxation approach for solving the related sample optimization problem. Computational results are provided to assess the efficiency of the proposed method