Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = DPIFWA

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
4717 KiB  
Article
Fuzzy Fireworks Algorithm Based on a Sparks Dispersion Measure
by Juan Barraza, Patricia Melin, Fevrier Valdez and Claudia I. Gonzalez
Algorithms 2017, 10(3), 83; https://doi.org/10.3390/a10030083 - 21 Jul 2017
Cited by 21 | Viewed by 6103
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 [...] Read more.
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). Full article
(This article belongs to the Special Issue Extensions to Type-1 Fuzzy Logic: Theory, Algorithms and Applications)
Show Figures

Figure 1

Back to TopTop