Karush-Kuhn-Tucker type optimality condition for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential
type: Item
instance of: scholarly article
title: Karush-Kuhn-Tucker type optimality condition for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential
zbMATH Open document ID: 1475.90131
author: Yanyan Li
published in: Journal of Global Optimization
publication date: 2021-04-28T00:00:00Z
review text: This work deals with the finite-dimensional constrained optimization problem of minimizing an objective function \(f\) on the set \(K=\{x\in \mathbb{R}^{n}:\,g_{i}(x)\leq 0,\,\forall i\in I\}\) where all functions \(f\) and \(g_{i}\), \(i\in I,\) are upper semicontinuous and essentially quasiconvex (that is, they have convex sublevel sets and every local minimum is global). The paper presents necessary and sufficient conditions for the optimality in terms of the Greenberg-Pierskalla subdifferential, which is a subdifferential that had previously used in quasiconvex analysis.
Mathematics Subject Classification ID: 90C56
Mathematics Subject Classification ID: 26B25
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C46
zbMATH DE Number: 7340740
zbMATH Keywords: optimality condition
zbMATH Keywords: quasiconvex programming
zbMATH Keywords: subdifferential
zbMATH Keywords: constraint qualification
reviewed by: A. Daniilidis
MaRDI profile type: Publication
full work available at URL: s10898-020-00926-8
OpenAlex ID: W3044808105
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DOI: 10.1007/S10898-020-00926-8
description: scientific article; zbMATH DE number 7340740