DocumentCode
170372
Title
ELA: A new swarm intelligence algorithm
Author
Yaosheng Sun ; Zhangcan Huang ; Yu Chen
Author_Institution
Sch. of Sci., Wuhan Univ. of Technol., Wuhan, China
fYear
2014
fDate
16-18 May 2014
Firstpage
109
Lastpage
113
Abstract
By analyzing the living behaviors of eels, this paper proposes a new eel swarm intelligence algorithm. This paper first describes the behavior of migratory eels, extracts three important behaviors-density adaption, neighboring learning and sex mutation, and establishes a model for the mathematical description of the three important behaviors. Based on rational organization of the three important behaviors, the eel algorithm is designed for continuous optimization problems. Finally, we test the performance of eel swarm intelligence algorithm via several selected benchmark problems. The results show that the algorithm, in terms of its excellent convergence speed and solving accuracy, is competitive to the compared algorithms.
Keywords
biology computing; optimisation; swarm intelligence; ELA; behaviors-density adaption; mathematical description; migratory eels; neighboring learning; optimization problems; rational organization; sex mutation; swarm intelligence algorithm; Algorithm design and analysis; Benchmark testing; Optimization; Particle swarm optimization; Signal processing algorithms; Sociology; Statistics; continuous algorithm; heuristic search algorithms; migration behavior; optimization problem; swarm intelligence algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Progress in Informatics and Computing (PIC), 2014 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-2033-4
Type
conf
DOI
10.1109/PIC.2014.6972306
Filename
6972306
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