An Adaptive Projection Gradient Method for Solving Nonlinear Fractional Programming

In this study, we focus on solving the nonlinear fractional optimization problem in which numerator is smooth convex and denominator concave. To achieve goal, develop an algorithm called adaptive projection gradient method. The main advantage of method that it allows computations for gradients considered functions metric to take place separately. Moreover, interesting property distinguishes proposed from some existing methods nonincreasing its step-size sequence. also prove sequence iterates generated by converges a solution derive rate convergence. illustrate performance efficiency our algorithm, numerical experiments are performed.