Analysis and research models of the Estimation of Distribution Algorithms

Author

Bi, Lihong ; Zhang, Shumin

Author_Institution

Shijiangzhuang Inst. of Railway Technol., Shijiangzhuang, China

Volume

3

fYear

2011

fDate

24-26 Dec. 2011

Firstpage

2014

Lastpage

2018

Abstract

The Estimation of Distribution Algorithms (EDAs) is a novel class of evolutionary algorithms which is motivated by the idea of building probabilistic graphical model of promising solutions to represent linkage information between variables in chromosome. Through learning of and sampling from probabilistic graphical model, new population is generated and optimization procedure is repeated until the stopping criteria are met. In this paper, the mechanism of the Estimation of Distribution Algorithms is analyzed. Currently existing EDAs are surveyed and categorized according to the probabilistic model they used, then the strengths and weakness and the future perspective of EDAs are concluded.

Keywords

evolutionary computation; genetics; learning (artificial intelligence); sampling methods; statistical distributions; analysis model; estimation of distribution algorithms; evolutionary algorithms; linkage information represent; optimization procedure; probabilistic graphical model; research models; sampling method; stopping criteria; Algorithm design and analysis; Bayesian methods; Estimation; Genetic algorithms; Optimization; Probabilistic logic; Probability distribution; Estimation of Distribution Algorithms; Genetic Algorithms; Probabilistic Graphical Model;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Network Technology (ICCSNT), 2011 International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4577-1586-0

Type

conf

DOI

10.1109/ICCSNT.2011.6182366

Filename

6182366