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Quadratic problems with two quadratic constraints: Convex quadratic relaxation and strong lagrangian duality

المؤلفHamdi, A.
المؤلفTaati, A.
المؤلفAlmaadeed, T.A.
تاريخ الإتاحة2023-09-24T07:55:31Z
تاريخ النشر2021
اسم المنشورRAIRO - Operations Research
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1051/ro/2020130
معرّف المصادر الموحدhttp://hdl.handle.net/10576/47869
الملخصIn this paper, we study a nonconvex quadratic minimization problem with two quadratic constraints, one of which being convex. We introduce two convex quadratic relaxations (CQRs) and discuss cases, where the problem is equivalent to exactly one of the CQRs. Particularly, we show that the global optimal solution can be recovered from an optimal solution of the CQRs. Through this equivalence, we introduce new conditions under which the problem enjoys strong Lagrangian duality, generalizing the recent condition in the literature. Finally, under the new conditions, we present necessary and sufficient conditions for global optimality of the problem. EDP Sciences, ROADEF, SMAI 2021.
راعي المشروعAcknowledgements. The authors are grateful to the referees for valuable comments and suggestions that helped us improve this article. The authors would like to thank Qatar University for the full support under the Grant NCBP-QUCP-CAS-2020-1.
اللغةen
الناشرEDP Sciences
الموضوعConvex quadratic relaxation
Quadratically constrained quadratic programming
SDO-relaxation
Strong duality
العنوانQuadratic problems with two quadratic constraints: Convex quadratic relaxation and strong lagrangian duality
النوعArticle
الصفحاتS2905-S2922
رقم المجلد55
dc.accessType Abstract Only


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