A multi-population genetic algorithm approach for solving ill-posed problems

被引：0
|
作者：
N. S. Mera
L. Elliott
D. B. Ingham
机构：
[1] Energy and Resources Research Institute,Centre for Computational Fluid Dynamics
[2] University of Leeds,Department of Applied Mathematics
来源：
Computational Mechanics | 2004年 / 33卷
关键词：
Genetic algorithms; Ill-posed problem; Boundary detection; Cauchy problem;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we develop a multi-population genetic algorithm (GA) for regularizing nonlinear ill-posed problems. Real coded genetic algorithms are used for calculating the minimizers of the Tikhonov functional. The algorithm is based on evolving separate populations for various values of the regularization parameter. The rate of convergence of the algorithm is substantially increased by exchanging information between neighbouring populations by the process of migration.
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页码：254 / 262
页数：8
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