Perturbation Analysis of a Condition Number for Linear Systems
SIAM Journal on Matrix Analysis and Applications
Some perturbation theory for linear programming
Mathematical Programming: Series A and B
Error bounds in mathematical programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Global Error Bounds for Convex Multifunctions and Applications
Mathematics of Operations Research
Mathematical Programming: Series A and B
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This paper studies the existence of a uniform global error bound when a convex inequality g ≤ 0, where g is a closed proper convex function, is perturbed. The perturbation neighborhoods are defined by small arbitrary perturbations of the epigraph of its conjugate function. Under certain conditions, it is shown that for sufficiently small arbitrary perturbations the perturbed system is solvable and there exists a uniform global error bound if and only if g satisfies the Slater condition and the solution set is bounded or its recession function satisfies the Slater condition. The results are used to derive lower bounds on the distance to ill-posedness.