A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA

Gallagher, M. R. and Yuan, B. (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. In: G. G. Yen and S. M. Lucas, 2006 IEEE Congress on Evolutionary Computation. 2006 IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, Canada, (1585-1591). 16-21 July 2006.

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Author Gallagher, M. R.
Yuan, B.
Title of paper A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA
Conference name 2006 IEEE Congress on Evolutionary Computation (CEC 2006)
Conference location Vancouver, Canada
Conference dates 16-21 July 2006
Proceedings title 2006 IEEE Congress on Evolutionary Computation
Place of Publication Piscataway, NJ, U.S.A.
Publisher IEEE - Institute of Electrical Electronics Engineers Inc.
Publication Year 2006
Sub-type Fully published paper
DOI 10.1109/CEC.2006.1688497
ISBN 0-7803-9487-9
Editor G. G. Yen
S. M. Lucas
Start page 1585
End page 1591
Total pages 7
Collection year 2006
Language eng
Abstract/Summary This paper presents some initial attempts to mathematically model the dynamics of a continuous estimation of distribution algorithm (EDA) based on a Gaussian distribution and truncation selection. Case studies are conducted on both unimodal and multimodal problems to highlight the effectiveness of the proposed technique and explore some important properties of the EDA. With some general assumptions, we show that, for ID unimodal problems and with the (mu, lambda) scheme: (1). The behaviour of the EDA is dependent only on the general shape of the test function, rather than its specific form; (2). When initialized far from the global optimum, the EDA has a tendency to converge prematurely; (3). Given a certain selection pressure, there is a unique value for the proposed amplification parameter that could help the EDA achieve desirable performance; for ID multimodal problems: (1). The EDA could get stuck with the (mu, lambda) scheme; (2). The EDA will never get stuck with the (mu, lambda) scheme.
Subjects E1
290901 Electrical Engineering
660301 Electricity transmission
Keyword Gaussian distribution
ID unimodal problems
Evolutionary computation
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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Created: Thu, 23 Aug 2007, 22:33:12 EST