A Class Of Random Fuzzy Linear Programming And Its Applications

Uncertain programming provides modeling methods for optimizing problems under uncertain environment. In real-life decision problems there usually exist, many kinds of uncertainties, that is, there may be multifold uncertain variables. When dealing with these multifold uncertain infromation, people are used to relying on predicting models, then replacing uncertain parameters with deterministic quantities and replacing multifold uncertain parameters with onefold uncertain variables, which we can imagine may be a very dangerous way for decision-making, leave out much valuable information. Therefore, it's necessary to use multifold uncertain variables to describe multifold information.Random fuzzy variable is a kind of multifold uncertain variable. In many real decision-making and statistical problems, some parameters of the distribution functions of some random variables are unknown. If the values of them are provided as fuzzy variables by experts or decision makers on the basis of data analysis and experience, the random variables become random fuzzy variables. Random fuzzy programming is for the problems which include random fuzzy variables. The elastic data structure and choice pattern will boost the descriptive and adaptive capability of programming models. For example, when companies are making plans and predicting the demand of the customers and markets or some other important parameters, it is better to corporate the management experience into the predicting models.Hence, with summarizing the known researches on random fuzzy programming and its applications and other related fields, we propose a system of solutions...