A sufficient conditions for global quadratic optimization
This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient conditions of global optimality for such probl...
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| Published in | Croatian Operational Research Review Vol. 11; no. 1; pp. 11 - 19 |
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| Main Authors | , |
| Format | Journal Article Paper |
| Language | English |
| Published |
Zagreb
Croatian Operational Research Society (CRORS)
01.01.2020
Hrvatsko društvo za operacijska istraživanja Croatian Operational Research Society |
| Subjects | |
| Online Access | Get full text |
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| Abstract | This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient conditions of global optimality for such problems subject to linear equality and inequality constraints. We prove that when the set of KarushKuhn-Tucker triplets of this problem is convex, then a local minimizer is global. |
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| AbstractList | This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient conditions of global optimality for such problems subject to linear equality and inequality constraints. We prove that when the set of KarushKuhn-Tucker triplets of this problem is convex, then a local minimizer is global. This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient conditions of global optimality for such problems subject to linear equality and inequality constraints. We prove that when the set of Karush-Kuhn-Tucker triplets of this problem is convex, then a local minimizer is global. |
| Author | Naffouti, Mourad Baccari, Abdeljelil |
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| ContentType | Journal Article Paper |
| Copyright | 2020. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| DOI | 10.17535/crorr.2020.0002 |
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| SubjectTerms | Applied mathematics convex sets global optimality conditions Inequality Lagrange multiplier linear constraints Mathematical programming nonconvex quadratic optimization Optimization Quadratic programming Triplets |
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| Title | A sufficient conditions for global quadratic optimization |
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