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It combines Dinkelbach's approach with a method guaranteed to solve linearly constrained quadratic programming problems regardless of the definiteness of the ...
It combines Dinkelbach's approach with a method guaranteed to solve linearly constrained quadratic programming problems regardless of the definiteness of the ...
In Part I [10] a concave-convex fractional program is related to a convex program. In this way duality results in convex programming can immediately be extended ...
Dinkelbach's transform has an advantage as compared to Charnes-Cooper transform in the sense that no extra constraints are introduced. B. Proposed Quadratic ...
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Jul 11, 2024 · The idea of tackling quadratic fractional programming goes back to Dinkelbach [12] . His approach was used by various researchers to study ...
In this paper, we provide an algorithm for solving quadratic fractional programming problems with two quadratic constraints. In the outer iterations, we ...
Feb 18, 2014 · This paper considers a fractional programming problem (P) which minimizes a ratio of quadratic functions subject to a two-sided quadratic constraint.
Oct 25, 2016 · The Dinkelbach method solve nonlinear fractional programming problems, where the functions in the numerator and denominator are not necessarily quadratic and ...
It is shown that the algorithm converges superlinearly and often (locally) quadratically. A priori and a posteriori error estimates are derived. Using those ...
It is attempted to survey applications as well as solution methods in linear, quadratic and concave-convex fractional programming. In the first part we give ...