Optimal design of manufacturing/remanufacturing logistics network based on uncertain programming

To deal with optimal design problem of manufacturing/remanufacturing (M/R) logistics network under uncertain circumstance, a two-stage stochastic-fuzzy programming model is developed, which involves continuous distribution stochastic parameters and fuzzy triangle or tolerance parameters. With the help of the model, the following items can be computed such as the optimal sites and numbers of M/R factory, integrated center, distribution center and collection center, the quantities of logistics flow in the network and the minimum fee in the planning horizon. Applying the fuzzy chance-constrained programming approach, the proposed model is transformed into a pure stochastic programming model. To solve this model, a hybrid genetic algorithm is presented, the sample average approximation method is introduced, the optimal objective value approaching technique is presented, and the optimal design steps are summarized. Besides, the application of the proposed model is showed with an example.