Abstract
We derive necessary and sufficient conditions for optimality of a problem with a pseudoconvex objective function, provided that a finite number of solutions are known. In particular, we see that the gradient of the objective function at every minimizer is a product of some positive function and the gradient of the objective function at another fixed minimizer. We apply this condition to provide several complete characterizations of the solution sets of set-constrained and inequality-constrained nonlinear programming problems with pseudoconvex and second-order pseudoconvex objective functions in terms of a known solution. Additionally, we characterize the solution sets of the Stampacchia and Minty variational inequalities with a pseudomonotone-star map, provided that some solution is known.
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The author is thankful to the Editor-in-Chief Professor Franco Giannessi for his help concerning the presentation.
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Communicated by Vaithilingam Jeyakumar.
This research is partially supported by the TU Varna Grant No. 18/2012.
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Ivanov, V.I. Optimality Conditions and Characterizations of the Solution Sets in Generalized Convex Problems and Variational Inequalities. J Optim Theory Appl 158, 65–84 (2013). https://doi.org/10.1007/s10957-012-0243-y
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DOI: https://doi.org/10.1007/s10957-012-0243-y