## Optimization: Theory and Algorithms |

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### Contents

HYPERTANGENT CONES FOR A SPECIAL CUSS OF SETS | 10 |

A GENERALIZED CONCEPT OF CONJUGATION | 45 |

WELLPOSED SADDLE POINT PROBLEMS | 61 |

Copyright | |

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algebra algorithm applied approximation assumption closed half-spaces compact constraints containing G convergence Convex analysis convex functional convex optimization convex set COROLLARY defined definition denote equation equivalent exists F is l.s.c. finite free group function f G a subset GS satisfying H-convex half-spaces Hence holds inf h(G hypertangent implies inequality inf f(x inf h(G inf sup infimum Lagrangian LEMMA Let F level sets linear locally convex space lower semicontinuous M-m sequence marginally proper Math max inf method minimization obtain optimal solution optimization problem point for f properties Proposition 1.2 prove quasiconvex quasiconvex function radial real numbers Remark result saddle point problem spherical functions STRIPS CONTAINING subset of F subspace sup f(x sup inf h(y sup{h suppose supremum Theorem 1.1 theory topological spaces topology tranche unique saddle point Universite upper semicontinuous variational inequalities well-posed saddle point whence