A Kind Of Programming Models With Stochastic And Fuzzy Papameters And Their Research Methods

In this paper we study the optimization problems. We mainly discuss the model and algorithm of uncertain programming in order to enrich algorithm and the thought of modeling for solving uncertain programming problems.At first we considered the hybrid chance-constrained programming model with fuzzy and stochastic parameters, designed a mixed intelligent arithmetic by using the technique of combing the stochastic simulation with fuzzy simulation and particle swarm optimization algorithm to solve this kind of problems, examples of manufacturing decision problems showed that the programming model and algorithm are reasonable and efficient. Then we presented a hybrid programming model with stochastic expectation and chance-constraint by combining the expectation model and the chance-constrained programming model. And, as its use in the fuzzy condition, we also presented a hybrid programming model with fuzzy expectation and chance-constraint. Then we proved that the modelsare feasible by analyzing some practical examples. At the last part of this paper, we studied a hybrid linear programming model with stochastic and fuzzy parameters, designed a simplex method base on the stochastic simulation with fuzzy simulation, practical examples show that the hybrid algorithm we designed is useful and feasible.The research result of this paper expands the content of the uncertain programming and provides new algorithms for calculating uncertain programming problems and also provides new modeling thought for solving problems more realistic.