DocumentCode :
2459493
Title :
Analysis of Scalable Parallel Evolutionary Algorithms
Author :
He, Jun ; Yao, Xin
Author_Institution :
School of Computer Science, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K. and Scho ol of Computer Science, Beijing Jiaotong University, China. (Email: j.he@cs.bham.ac.uk)
fYear :
2006
fDate :
16-21 July 2006
Firstpage :
120
Lastpage :
127
Abstract :
Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at making an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evo lutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup.
Keywords :
Algorithm design and analysis; Computer science; Costs; Counting circuits; Evolutionary computation; Genetic mutations; Helium; Parallel machines; Parallel processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Print_ISBN :
0-7803-9487-9
Type :
conf
DOI :
10.1109/CEC.2006.1688298
Filename :
1688298
Link To Document :
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