scholarly journals A Review and Comparative Study of Firefly Algorithm and its Modified Versions

10.5772/62472 ◽  
2016 ◽  
Author(s):  
Waqar A. Khan ◽  
Nawaf N. Hamadneh ◽  
Surafel L. Tilahun ◽  
Jean M.T. Ngnotchouye
Keyword(s):  
Comparative Study ◽  
Firefly Algorithm

Comparative study of prey predator algorithm and firefly algorithm

2018 ◽  
Vol 24 (2) ◽  
pp. 359-366 ◽  
Author(s):  
Hong Choon Ong ◽  
Surafel Luleseged Tilahun ◽  
Wai Soon Lee ◽  
Jean Meadard T Ngnotchouye
Keyword(s):  
Comparative Study ◽  
Firefly Algorithm

scholarly journals Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

2018 ◽  
Vol 8 (3) ◽  
pp. 339 ◽  
Author(s):  
Mohamed Louzazni ◽  
Ahmed Khouya ◽  
Khalid Amechnoue ◽  
Alessandro Gandelli ◽  
Marco Mussetta ◽  
...  
Keyword(s):  
Comparative Study ◽  
Firefly Algorithm ◽  
Metaheuristic Algorithm ◽  
Photovoltaic Parameters

scholarly journals A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-Dong Zhou ◽  
Ting-Hua Yi ◽  
Huan Zhang ◽  
Hong-Nan Li
Keyword(s):  
Structural Health Monitoring ◽  
Comparative Study ◽  
Health Monitoring ◽  
Firefly Algorithm ◽  
Hamming Distance ◽  
Optimization Problems ◽  
High Reliability ◽  
Sensor Placement ◽  
Structural Health ◽  
Wide Range

Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems.

Sign in / Sign up

Export Citation Format

Share Document