SDO relaxation approach to fractional quadratic minimization with one quadratic constraint

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.

کلیدواژه ها:

Fractional quadratic optimization ، nonconvex problem ، convex optimization ، semidefinite optimization