Name
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) the selection strategy lead to the contribution of the firework with the best fitness (core firework) for the optimization overwhelms the contributions of the rest of fireworks (non-core fireworks) in the explosion operator, (ii) the Gaussian mutation operator is not as effective as it is designed to be. To overcome these limitations, the CoFFWA is proposed, which can greatly enhance the exploitation ability of non-core fireworks by using independent selection operator and increase the exploration capacity by crowdness-avoiding cooperative strategy among the fireworks. Experimental results on the CEC2013 benchmark functions suggest that CoFFWA outperforms the state-of-the-art FWA variants, artificial bee colony, differential evolution, the standard particle swarm optimization (SPSO) in 2007 and the most recent SPSO in 2011 in term of convergence. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TCBB.2015.2497227 | IEEE/ACM Trans. Comput. Biology Bioinform. |
Keywords | Field | DocType |
Fireworks algorithm,Gaussian processes,Particle swarm optimization,Algorithm design and analysis,Genetic algorithms | Convergence (routing),Particle swarm optimization,Mathematical optimization,Algorithm design,Computer science,Swarm intelligence,Differential evolution,Artificial intelligence,Operator (computer programming),Machine learning,Genetic algorithm,Fireworks | Journal |
Volume | Issue | ISSN |
14 | 1 | 1545-5963 |
Citations | PageRank | References |
13 | 0.61 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shaoqiu Zheng | 1 | 238 | 11.51 |
| Junzhi Li | 2 | 132 | 7.72 |
| Andreas Janecek | 3 | 216 | 12.74 |
| Ying Tan | 4 | 1286 | 95.40 |