## Decision models in stochastic programming: operational methods of decision making under uncertainty |

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### Contents

Estimation and Updating | 4 |

Value of Information in Decision Models | 43 |

MultipleCriteria Decisions | 80 |

Copyright | |

4 other sections not shown

### Common terms and phrases

applied approximately associated assumed assumption average best population characteristic roots characterize clear coefficients complementary eigenvalue problems computed conditional consider constraints Corollary cost function covariance covariance matrix decision maker decision problem decision variables defined denotes diagonal economic eigenvector elements equation estimates exists expected given Hence homoscedastic inventory linear decision rules linear programming LP models LP problem maximizes maximum methods minimax minimize minimum mixed strategies multivariate normal Nash-equilibrium nonlinear program nonnegative nonzero normal distribution null hypothesis objective function observations optimal decision vector output pair parameters payoff Player positive definite preassigned probability distribution production profits pure strategies quadratic game quasi-polynomial random respectively risk aversion risk preference function sample satisfy scalar selection shadow prices specification statistic stochastic components stochastic linear programming stochastic programming strategy vectors Theorem theory tion unsanded utility function variance variance-covariance matrix zero