Some perturbation theory for linear programming
Mathematical Programming: Series A and B
Stability and Well-Posedness in Linear Semi-Infinite Programming
SIAM Journal on Optimization
Distance to ill-posedness and the consistency value of linear semi-infinite inequality systems
Mathematical Programming: Series A and B
Distance to Solvability/Unsolvability in Linear Optimization
SIAM Journal on Optimization
Mathematics of Operations Research
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This paper studies certain Lipschitz properties of the optimal value function of a linear semi-infinite programming problem and its dual problem in the sense of Haar. In this setting, it is already known that the optimal value function of the so-called primal problem was Lipschitz continuous around a given stable solvable problem, when perturbations of all the coefficients are allowed. Recently, a Lipschitz constant, depending only on the nominal problem data, has been computed and, the no duality gap under certain stability conditions ensures moreover that the obtained constant still holds for the dual optimal value function. Our approach here is focused on obtaining Lipschitz constants for both primal and dual optimal value functions under weaker hypothesis of stability, which do not preclude, in all the cases, the existence of duality gap. Now, the allowed perturbations are restricted to the coefficients of the objective function of the corresponding problems.