## Stochastic programming with multiple objective functions |

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### Contents

Introduction | 1 |

with several objective functions | 7 |

Stochastic programming with one objective | 71 |

Copyright | |

7 other sections not shown

### Common terms and phrases

algorithm Assume Bereanu blem boundary hyperplane Chapter Charnes coefficients Consider constraints convex convex function convex programming convex set covariance matrix criterion decision-maker defined Denote determine deterministic equivalent distribution function domain of feasible efficiency functions efficient solutions exists feasible solutions Fk(x function F given goal programming Hence Kataoka's problem Lebesgue measure Lemma linear functions linear programming problem m n p mathematical programming problem maximization maximum mean value method minimization minimum minimum-risk problem multiple minimum-risk solution multiple objective functions normal distribution obtained optimal solution optimum value P{co parameters parametric programming probability distribution probability space problem max problem with multiple production programming with multiple proof is complete quadratic programming random vector solution of Problem solve Problem Stancu-Minasian stochastic linear programming stochastic programming problem subject to Ax synthesis function Theorem tion utility function x'Vx