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A Cooperative Framework for Fireworks Algorithm.
- Source :
- IEEE/ACM Transactions on Computational Biology & Bioinformatics; Jan/Feb2017, Vol. 14 Issue 1, p27-41, 15p
- Publication Year :
- 2017
-
Abstract
- This paper presents a cooperative framework for fireworks algorithm (CoFFWA). A detailed analysis of existing fireworks algorithm (FWA) and its recently developed variants has revealed that ( $i$<alternatives><inline-graphic xlink:href="zheng-ieq1-2497227.gif"/> </alternatives>) the current selection strategy has the drawback that the contribution of the firework with the best fitness (denoted as core firework) overwhelms the contributions of all other fireworks (non-core fireworks) in the explosion operator, ($ii$<alternatives> <inline-graphic xlink:href="zheng-ieq2-2497227.gif"/></alternatives>) the Gaussian mutation operator is not as effective as it is designed to be. To overcome these limitations, the CoFFWA is proposed, which significantly improves the exploitation capability by using an independent selection method and also increases the exploration capability by incorporating a crowdness-avoiding cooperative strategy among the fireworks. Experimental results on the CEC2013 benchmark functions indicate that CoFFWA outperforms the state-of-the-art FWA variants, artificial bee colony, differential evolution, and the standard particle swarm optimization SPSO2007/SPSO2011 in terms of convergence performance. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 15455963
- Volume :
- 14
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- IEEE/ACM Transactions on Computational Biology & Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 121196566
- Full Text :
- https://doi.org/10.1109/TCBB.2015.2497227