An optimization Model and its Solution Algorithm for Distribution Network Design Problem with uncertainty demand

Based on the uncertainty characteristic about produce in the plant and demand of customer, a fuzzy chance constrained programming optimization model is presented. In the proposed model, the stochastic variables are converted into fuzzy parameters by a new method. Then, a revised hybrid genetic algorithm is developed to solve the proposed model, which are transformed into three classical transportation sub- problems according to the specialty of the optimization model. And the algorithm is implemented under the Visual C++ development environment by a numerical example. From the result of simulation, the given algorithm is valid to the large-scale logistics network optimization model with uncertainty demand.