Genetic algorithms for modelling and optimisation
Genetic algorithms for modelling and optimisation
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DOI：
10.1016/j.cam.2004.07.034
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发表时间：
2005-12-01
影响因子：
2.4
通讯作者：
McCall, J
中科院分区：
文献类型：
--
作者：
McCall, J
遗传算法是一种受自然进化启发的启发式搜索和优化技术。它们已经成功地应用于各种复杂的现实世界问题。本文旨在为对免疫学感兴趣的免疫学家和数学家介绍GAS。在推测性地确定遗传算法在免疫学研究中的可能应用之前，我们描述了如何构建遗传算法和遗传算法理论的主要分支。最后给出了遗传算法在医学最优控制问题中的应用实例。本文还简要介绍了人工免疫系统的相关领域。(C)2005 Elsevier B.V.保留所有权利。
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.