## Applied Mathematical Programming and Modeling IV: APMOD 98 |

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### Contents

Preface | 13 |

Foreword | 21 |

PrimalDual Constraint Aggregation with Application to Stochastic Programming | 41 |

Copyright | |

21 other sections not shown

### Common terms and phrases

A/-scenarios active set aggregation algorithm analysis applied approach approximate asset bond capacity coefficients components computational considered constraints convergence convex corresponding CPLEX cutting plane data set decision variables defined denote distribution dynamic equation error evaluation feasible first-stage fixed costs flexibility formulation geometric Brownian motion heuristic hyperplane implementation index set initial integer linear programming interior point interior point methods investment Italian Liras knapsack problem Lagrangian lattice learning lemma linear programming lower bound machine Mathematical Programming maximize maximum MILP multistage stochastic Newton step node objective function obtained Operations Research optimal solution optimal value optimization problem option paper parallel parameters polytope portfolio selection primal-dual procedure production programming problems Proof quadratic random replacement reservoir volume risk scenario tree simulation solve stochastic optimization stochastic programming strategy subproblems theorem tion transaction costs tuple uncertainty University update upper bound vector yield yield curve