Genetic algorithms for modelling and optimisation

被引：599
|
作者：
McCall, J [1 ]
机构：
[1] Robert Gordon Univ, Sch Comp, Aberdeen AB9 1FR, Scotland
来源：
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2005年 / 184卷 / 01期
关键词：
genetic algorithms; immunology; optimisation; evolution;
D O I：
10.1016/j.cam.2004.07.034
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by natural evolution. They have been successfully applied to a wide range of real-world problems of significant complexity. This paper is intended as an introduction to GAs aimed at immunologists and mathematicians interested in immunology. We describe how to construct a GA and the main strands of GA theory before speculatively identifying possible applications of GAs to the study of immunology. An illustrative example of using a GA for a medical optimal control problem is provided. The paper also includes a brief account of the related area of artificial immune systems. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：205 / 222
页数：18
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