Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints

被引:13
作者
Lozada-Chang, Li-Vang [3 ]
Santana, Roberto [1 ,2 ]
机构
[1] Univ Basque Country, Intelligent Syst Grp, Dept Comp Sci & Artificial Intelligence, San Sebastian, Spain
[2] Univ Politecn Madrid, E-28660 Madrid, Spain
[3] Univ Havana, Fac Math & Computat, Havana, Cuba
关键词
Estimation of distribution algorithms; Univariate marginal distribution algorithm; Convergence analysis; Evolutionary algorithms; Long string limit analysis;
D O I
10.1016/j.ins.2011.01.024
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we introduce a mathematical model for analyzing the dynamics of the univariate marginal distribution algorithm (UMDA) for a class of parametric functions with isolated global optima. We prove a number of results that are used to model the evolution of UMDA probability distributions for this class of functions. We show that a theoretical analysis can assess the effect of the function parameters on the convergence and rate of convergence of UMDA. We also introduce for the first time a long string limit analysis of UMDA. Finally, we relate the results to ongoing research on the application of the estimation of distribution algorithms for problems with unitation constraints. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:2340 / 2355
页数:16
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