Optimization for Production/Remanufacturing System with Return Rate Dependent on Price and Quality under Uncertainty

In this paper, an integrated production/remanufacturing system is investigated, in which the relationship of return rate, price and acceptable quality follows Mamdani fuzzy rule based on the experience. The uncertainty of customer demand is also considered and supposed to be a type of triangular fuzzy variable. Then, a fuzzy chance programming is developed to optimize the total cost at a confidence level by determining the decision parameters of purchasing price and acceptable quality and intermediate parameter of return rate for returns. An approximation algorithm using particle swarm optimization (PSO) and fuzzy simulation is then presented to compute the optimization problem effectively. Finally, the experiment result shows the efficiency of the proposed approach.