Sample Average Approximation Method for Chance Constrained Stochastic Programming in Transportation Model of Emergency Management

In this paper, an optimal model for the transportation of emergency resource is established on chance constrained stochastic programming. We use Conditional Value at Risk (CVaR) to approximate the chance constraint, and we get the approximation problem of the chance constrained stochastic programming by using the sample average approximation (SAA) method. For a given sample, the SAA problem is a deterministic nonlinear programming (NLP) and any appropriate NLP code can be applied to solve the problem. The model and method provide a new way for the emergency logistics management engineering.