Genetic algorithms for modelling and optimisation

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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.

论文关键词:68T05,92B05,49-04,92D15,Genetic algorithms,Immunology,Optimisation,Evolution

论文评审过程:Received 27 February 2004, Revised 7 July 2004, Available online 8 April 2005.

论文官网地址:https://doi.org/10.1016/j.cam.2004.07.034