免疫万有引力搜索算法的研究与仿真

摘要

受生物体免疫系统免疫机制的启发,利用免疫信息处理机制来改善万有引力搜索算法(gravitational search algorithm,GSA)的局部优化性能,提出了免疫GSA.该算法结合了GSA全局寻优能力和免疫系统免疫信息处理机制的优点,并且实现简单,改善了GSA摆脱局部极值点的能力,提高了算法进化过程中的收敛速度和精度.通过仿真算例对提出的算法进行了验证,结果表明:提出的免疫GSA的性能优于原GSA.%Inspired by the immune mechanism of organisms immune system, the local optimize performance of gravitational search algorithm ( GSA ) was improved by the immune information processing mechanism, and the GSA with immunity was proposed. The proposed algorithms have both the advantages of the original GSA and the immune information processing mechanism of immune system, which can improve the abilities of seeking the global excellent result and evolution speed. The computer simulation result in examples demonstrates that the proposed algorithms are superior to the original GSA.