Stability, Duality and Decomposition in General Mathematical Programming |
Contents
Prologue | 5 |
Some basic definitions and results | 23 |
Continuity of feasible set maps | 37 |
Copyright | |
8 other sections not shown
Common terms and phrases
accumulation point additively separable affine functions algorithm arbitrarily chosen asymptotic convergence CD(g closedness codomain compact set considered Constraint Decomposition constraint functions continuous w.r.t. convex set Dantzig-Wolfe Decomposition defined denoted dual programme dual solutions dual subprogrammes duality theory e-optimal Euclidean spaces feasible set map feasible solution finite convergence finite number follows function G Furthermore Geoffrion Hogan implies Integer Linear Programming iteration Lemma lim inf lim sup lower bounds lower semi-continuous Mathematical Programming MF-regular mixed-integer non-linear Nonlinear Programming notion number of steps objective function ºº optimal solution value optimization problem point-to-set map primal and dual primal programme primal solutions primal subprogrammes Proof prove real-valued relaxed master programmes respect restricted result right-hand-side perturbations Section sequence solution g stability strictly quasi-convex strong duality Subsection Suppose Theorem 3.3 tion upper bounds upper semi-continuous value-function variable decomposition procedure