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SDO relaxation approach to fractional quadratic minimization with one quadratic constraint | ||
| Journal of Mathematical Modeling | ||
| مقاله 1، دوره 3، شماره 1، شهریور 2015، صفحه 1-13 اصل مقاله (134.3 K) | ||
| نوع مقاله: Research Article | ||
| نویسندگان | ||
| Maziar Salahi* ؛ Arezo Zare | ||
| Faculty of Mathematical Sciences, University of Guilan,Rasht, Iran | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Fractional quadratic optimization؛ nonconvex problem؛ convex optimization؛ semidefinite optimization | ||
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آمار تعداد مشاهده مقاله: 2,087 تعداد دریافت فایل اصل مقاله: 2,213 |
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