Volume 55, 2021Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
|Page(s)||S2241 - S2258|
|Published online||02 March 2021|
SDO and LDO relaxation approaches to complex fractional quadratic optimization
Department of Mathematics, Statistics and Computer Science, Semnan University, Semnan, Iran
* Corresponding author: firstname.lastname@example.org
Accepted: 18 August 2020
This paper examines a complex fractional quadratic optimization problem subject to two quadratic constraints. The original problem is transformed into a parametric quadratic programming problem by the well-known classical Dinkelbach method. Then a semidefinite and Lagrangian dual optimization approaches are presented to solve the nonconvex parametric problem at each iteration of the bisection and generalized Newton algorithms. Finally, the numerical results demonstrate the effectiveness of the proposed approaches.
Mathematics Subject Classification: 90C32 / 90C26 / 90C22
Key words: Fractional quadratic optimization / nonconvex problem / semidefinite programming / Lagrangian dual optimization
© EDP Sciences, ROADEF, SMAI 2021
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