Approximation To Fuzzy Programming Problem And Its Solutions

This thesis firstly defines the uniform integrability and absolute continuity of fuzzy variables, discusses their relationships, and provides an approach to checking the uniform integrability of fuzzy variables. Then, based on credibility theory a new kind of fuzzy two-stage minimum-risk model is proposed and its deterministic equivalent programming problems are discussed. Furthermore, the issues of the approximation of credibility function and the convergence of the approximation method are treated. In order to solve the proposed model we design a heuristic algorithm which incorporates approximation method, NN and simulated annealing. Finally, the fuzzy two-stage minimum-risk model is applied to the location-allocation problem.The main work of this thesis can be summarized as the following:(i) The uniform integrability and absolute continuity for a family of fuzzy variables are defined and their links are also considered.(ii) A new class of fuzzy two-stage minimum-risk model is proposed. The approximation of credibility function and the convergence of approximation method are discussed.(iii) A hybrid intelligent algorithm based on approximation method, NN and simulated annealing is designed to solve the general fuzzy two-stage minimum-risk model, and the application of the proposed model to location-allocation problem is considered.