Fractional programming
S Schaible - Handbook of global optimization, 1995 - Springer
An introduction to ratio optimization problems is provided which covers various applications
as well as major theoretical and algorithmic developments. In addition to an extensive …
as well as major theoretical and algorithmic developments. In addition to an extensive …
A fifth bibliography of fractional programming
IM Stancu-Minasian - Optimization, 1999 - Taylor & Francis
This bibliography of fractional programming is a continuation of four previous bibliographies
by the author (Pure Appl. Math. Sci.(India), Vol. XIII, No. 1-2, 35-69, March (1981); ibid. Vol …
by the author (Pure Appl. Math. Sci.(India), Vol. XIII, No. 1-2, 35-69, March (1981); ibid. Vol …
Revisiting Dinkelbach-type algorithms for generalized fractional programs
JP Crouzeix, JA Ferland, H Van Nguyen - Opsearch, 2008 - Springer
In this paper we introduce a new Dinkelbach-type algorithm where the new iterate is
determined using the information given by previous iterates and not only by the last one. The …
determined using the information given by previous iterates and not only by the last one. The …
[HTML][HTML] Revisiting Karnik–Mendel algorithms in the framework of linear fractional programming
T Kumbasar - International Journal of Approximate Reasoning, 2017 - Elsevier
Abstract For Interval Type-2 (IT2) fuzzy sets and systems, calculating the centroid and
performing type reduction are operations that must be taken into consideration. The Karnik …
performing type reduction are operations that must be taken into consideration. The Karnik …
A globally convergent method for solving nonlinear equations without the differentiability condition
A Pietrus - Numerical Algorithms, 1996 - Springer
We give a general iterative method which computes the maximal real root x max of a one
variable Lipschitzian function in a given interval. The method generates a monotonically …
variable Lipschitzian function in a given interval. The method generates a monotonically …
[PDF][PDF] TAUX DE CONVERGENCE D'UNE GENERALISATION DE LA METHODE DE NEWTON: PREMIERE PARTIE
Y BENADADA - Une - dyna.maths.free.fr
Motivation: La méthode de Newton pour trouver le zéro de l'équation g (x)= 0 peut être
facilement généralisée au cas où g est monotone, convexe, mais pas forcément …
facilement généralisée au cas où g est monotone, convexe, mais pas forcément …