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

页码：205 / 222

页数：18

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