Title
Improve enhanced fireworks algorithm with differential mutation
Abstract
Fireworks algorithm (FWA) is a newly proposed swarm intelligence algorithm, which is used to solve optimization problems. However, the interaction of fireworks in FWA is not sufficient. In this paper, the differential mutation operator is introduced to improve the interaction mechanism of enhanced FWA (EFWA), which is the latest version of FWA. Extensive experiments on 30 benchmark functions were conducted to test the performance of the new algorithm named enhanced fireworks algorithm with differential mutation (FWA-DM). Experimental results have shown that differential mutation operator is able to improve EFWA.
Year
DOI
Venue
2014
10.1109/SMC.2014.6973918
SMC
Keywords
Field
DocType
swarm intelligence algorithm,evolutionary computation,enhanced fwa interaction mechanism,enhanced fireworks algorithm,differential mutation operator,fwa-dm algorithm,swarm intelligence
Computer science,Fireworks algorithm,Swarm intelligence,Artificial intelligence,Fireworks,Mutation operator
Conference
ISSN
Citations 
PageRank 
1062-922X
8
0.49
References 
Authors
14
3
Name
Order
Citations
PageRank
Chao Yu1453.04
Junzhi Li21327.72
Ying Tan3128695.40