Title
Fuzzy Fireworks Algorithm Based on a Sparks Dispersion Measure.
Abstract
The main goal of this paper is to improve the performance of the Fireworks Algorithm (FWA). To improve the performance of the FWA we propose three modifications: the first modification is to change the stopping criteria, this is to say, previously, the number of function evaluations was utilized as a stopping criteria, and we decided to change this to specify a particular number of iterations; the second and third modifications consist on introducing a dispersion metric (dispersion percent), and both modifications were made with the goal of achieving dynamic adaptation of the two parameters in the algorithm. The parameters that were controlled are the explosion amplitude and the number of sparks, and it is worth mentioning that the control of these parameters is based on a fuzzy logic approach. To measure the impact of these modifications, we perform experiments with 14 benchmark functions and a comparative study shows the advantage of the proposed approach. We decided to call the proposed algorithms Iterative Fireworks Algorithm (IFWA) and two variants of the Dispersion Percent Iterative Fuzzy Fireworks Algorithm (DPIFWA-I and DPIFWA-II, respectively).
Year
DOI
Venue
2017
10.3390/a10030083
ALGORITHMS
Keywords
Field
DocType
fuzzy logic,dynamic adaptation,dispersion percent,FWA,IFFWA,DPIFWA
Dispersion (optics),Mathematical optimization,Fireworks algorithm,Fuzzy logic,Algorithm,Artificial intelligence,Mathematics,Machine learning
Journal
Volume
Issue
Citations 
10
3
0
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Juan Barraza100.34
Patricia Melin24009259.43
Fevrier Valdez395257.96
Claudia I. González419910.78