Abstract
Mathematical programming has been applied to many problems in various fields. The data of real problems contain uncertainty and are thus represented as random variables. Decision-making under conditions of uncertainty involves potential risk. Stochastic programming deals with optimization under uncertainty. A stochastic programming problem with recourse is referred to as a twostage stochastic problem. In this paper, the stochastic programming model for the logistics network reorganization problem and the efficient solution method are shown. The traditional expected cost model and the CVaR model are compared in numerical experiments. The expected cost rises slightly using the CVaR as the objective. However, it is shown that the worst cost is reduced using the CVaR.