Differential stability properties in scalar and vector convex optimization

C. Gutiérrez Vaquero, D. T. V. An

The paper addresses formulas for the $\varepsilon$-subdifferential of the optimal value function of scalar and vector convex optimization problems, which work in the case where the solution set of the problem is empty. In scalar optimization problems with an inclusion constraint, a limiting formula is obtained, which does not require any constraint qualification. In vector optimization problems, exact formulas are derived by linear scalarization and an $\varepsilon$-subdifferential due to Taa.

Keywords: Differential stability, $\varepsilon$-subdifferential, limiting calculus rule, optimal value function, approximate solution, vector optimization, infimal set, weak minimal solution

Scheduled

GT11 Continuous Optimization III
June 9, 2022  5:10 PM
A12

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A unified concept of approximate and quasi efficient solutions in multiobjective optimization

L. Huerga Pastor, B. Jiménez Martín, D. T. Luc, V. Novo

A reformulation on a product space with reduced dimension for splitting algorithms

R. Campoy García

A new Lagrange-type duality approach in set-valued convex programming based on pointed closed convex processes

M. A. Melguizo Padial, F. García Castaño

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