@article { author = {Salahi, Maziar and Zare, Arezo}, title = {SDO relaxation approach to fractional quadratic minimization with one quadratic constraint}, journal = {Journal of Mathematical Modeling}, volume = {3}, number = {1}, pages = {1-13}, year = {2015}, publisher = {University of Guilan}, issn = {2345-394X}, eissn = {2382-9869}, doi = {}, abstract = {In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to a quadratic constraint. First we introduce a parametric equivalent of the problem. Then a bisection and a generalized Newton-based method algorithms are presented to solve it. In order to solve the quadratically constrained quadratic minimization problem within both algorithms, a semidefinite optimization relaxation approach is presented. Finally, two set of examples are presented to compare the performance of algorithms.}, keywords = {Fractional quadratic optimization,nonconvex problem,convex optimization,semidefinite optimization}, url = {https://jmm.guilan.ac.ir/article_198.html}, eprint = {https://jmm.guilan.ac.ir/article_198_2afefd8e0fbd7908279afb268bcdcf96.pdf} }