Parametric Evaluation and Mean-Standard Deviation Analysis in Stochastic Programming Models.
CARNEGIE-MELLON UNIV PITTSBURGH PA MANAGEMENT SCIENCES RESEARCH GROUP
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The main interest is in investigating several kinds of implications of stochastic programming models and their uses to provide several types of dialogues between formal models and the decision maker himself under risk-taking situations. First, some stochastic programming models which are often discussed in the literature are presented and parametric evaluations using dual evaluators are attempted. Second, we see a close relationship between these models and the mean-standard deviation analysis mainly developed in the context of portfolio selection theory. Third, we explore utility implications of these models in connection with the expected utility maximization principle. Finally, attempts are made to impute the values of key parameters in each of these models and some other utility models from the actual decision made in the mean-standard devication analysis of framework. Author
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