Abstract:
The article studies models and methods for solving possibilistic-probabilistic programming tasks where strongest and weakest t-norms are used to describe interaction between parameters of fuzzy optimization model. Different principles of decision making under hybrid possibilistic-probabilistic uncertainty are investigated.
Keywords:Possibilistic-probabilistic optimization, possibilistic random variable, t-norm, expected value of fuzzy random variable, possibility measure, restrictions on possibility and probability, inderect method, direct method.