Title of article :
Performance evaluation of firefly algorithm with unconstrained optimization issues
Author/Authors :
Sulaiman Khaleel, Elaf Faculty of Computer Sciences and Mathematics - University of Mosul, Iraq , Al-Naemi, Ghada M Faculty of Computer Sciences and Mathematics - University of Mosul, Iraq , Hamed, Eman T Faculty of Computer Sciences and Mathematics - University of Mosul, Iraq , Ahmed, Huda I Faculty of Computer Sciences and Mathematics - University of Mosul, Iraq
Abstract :
In this paper, we have investigated a new spectral Quasi-Newton (QN) algorithm. New search
directions of the proposed algorithm increase its stability and increase the arrival to the optimum
solution with a lowest cost value and our numerical applications on the standard Fire
y Algorithm
(FA)and the new proposed algorithm are powerful as in meta-heuristic field. Our new proposed
algorithm has quite common uses in several sciences and engineering problems. Finally, our numerical
results show that the proposed technique is the best and its accuracy higher than the accuracy of
the standard FA. These numerical results are compared using statistical analysis to evaluate the
effciency and the robustness of new proposed algorithm.
Keywords :
QN-method , conjugate gradient , unconstrained Optimization , self-scaling QN
Journal title :
International Journal of Nonlinear Analysis and Applications