Approximate Optimality and Approximate Duality for Quasi Approximate Solutions in Robust Convex Semidefinite Programs

Liguo Jiao () and Jae Hyoung Lee ()
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Liguo Jiao: Pukyong National University
Jae Hyoung Lee: Pukyong National University

Journal of Optimization Theory and Applications, 2018, vol. 176, issue 1, No 5, 74-93

Abstract: Abstract In this paper, we study quasi approximate solutions for a convex semidefinite programming problem in the face of data uncertainty. Using the robust optimization approach (worst-case approach), approximate optimality conditions and approximate duality theorems for quasi approximate solutions in robust convex semidefinite programming problems are explored under the robust characteristic cone constraint qualification. Moreover, some examples are given to illustrate the obtained results.

Keywords: Robust convex semidefinite programming problems; Quasi approximate solutions; Robust characteristic cone constraint qualification; Approximate optimality conditions; Approximate duality theorems; 90C22; 90C46; 90C31 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10957-017-1199-8

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