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 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

scholarly journals A New Modified Firefly Algorithm

2016 ◽  
Vol 4 (2) ◽  
pp. 18 ◽  
Author(s):  
Medha Gupta ◽  
Divya Gupta
Keyword(s):  
Firefly Algorithm ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Collective Intelligence ◽  
Metaheuristic Algorithm ◽  
Numerical Studies ◽  
Modified Firefly Algorithm

<p class="Abstract"><span lang="EN-GB">Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. </span><span lang="EN-AU">Firefly Algorithm is one of the new such swarm-based metaheuristic algorithm inspired by the flashing behavior of fireflies. The algorithm was first proposed in 2008 and since then has been successfully used for solving various optimization problems. In this work, we intend to propose a new modified version of Firefly algorithm (MoFA) and later its performance is compared with the standard firefly algorithm along with various other meta-heuristic algorithms. Numerical studies and results demonstrate that the proposed algorithm is superior to existing algorithms.</span></p>

Chaos-Enhanced Firefly Algorithm with Automatic Parameter Tuning

2011 ◽  
Vol 2 (4) ◽  
pp. 1-11 ◽  
Author(s):  
Xin-She Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Design Problem ◽  
Firefly Algorithm ◽  
Parameter Tuning ◽  
Population Based ◽  
Metaheuristic Algorithms ◽  
Metaheuristic Algorithm ◽  
Swarm Optimization ◽  
New Algorithms ◽  
Automatic Parameter Tuning

Many metaheuristic algorithms are nature-inspired, and most are population-based. Particle swarm optimization is a good example as an efficient metaheuristic algorithm. Inspired by PSO, many new algorithms have been developed in recent years. For example, firefly algorithm was inspired by the flashing behaviour of fireflies. In this paper, the author extends the standard firefly algorithm further to introduce chaos-enhanced firefly algorithm with automatic parameter tuning, which results in two more variants of FA. The author first compares the performance of these algorithms, and then uses them to solve a benchmark design problem in engineering. Results obtained by other methods will be compared and analyzed.

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
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