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
Link To Document :
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