摘要
免疫遗传算法在传统遗传算法的全局随机搜索的基础上,借鉴生物免疫机制中的抗体的多样性,能有效提高群体的多样性,同时其具有记忆功能能够有效地提高搜索效率。但是在函数优化问题的解决上,免疫记忆功能一直没有能很好的实现。该文提出在免疫遗传算法中引入模式控制的方法来解决复杂函数优化的问题。基于免疫遗传机制,利用免疫记忆库记忆优秀免疫遗传模式,它能有效地加速优化过程,并且克服通常函数优化无缺乏记忆的功能。通过一个复杂函数的仿真实例证明了该方法的有效性。
Immune Genetic Algorithm, based on general genetic algorithm, which has the perpetuity of global searching and diversity of the biological immune mechanism, can advance the diversity of evolution group effectively, and its memory function can improve the searching efficiency. However, immune memory function for function optimization has not been realized validly yet. This paper introduces a schema control method for immune genetic algorithm to solve the complex function optimization. Based on immune genetic mechanism, it uses vaccines bank to memorize excellent IGA schema in order to validly accelerate the optimization process, and make general function optimization have the memory function. The experimental results prove that this algorithm has good performance.
出处
《计算机仿真》
CSCD
2005年第8期98-100,114,共4页
Computer Simulation
关键词
免疫
模式控制
函数优化
Immune
Schema control
Function optimization
