机构地区: 广州大学计算机科学与教育软件学院计算机科学系
出 处: 《计算机工程与应用》 2004年第6期4-6,33,共4页
摘 要: 受生物体免疫系统免疫机制的启发,论文把免疫系统的免疫信息处理机制引入到粒子群优化算法中,给出了免疫粒子群优化算法。这种免疫粒子群优化算法结合了粒子群优化算法具有的全局寻优能力和免疫系统的免疫信息处理机制,并且实现简单,改善了粒子群优化算法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。一个求多维函数最优值的计算机仿真对比结果表明,免疫粒子群优化算法的收敛性能优于粒子群优化算法。 In this paper,the immune information processing mechanism of immune system is involved into original par-ticle swarm optimizer,and the particle swarm optimization algorithms with immunity are proposed.The proposed algo-rithms have both the properties of the original particle swarm optimization algorithm and the immune mechanism of im-mune system,can improve the abilities of seeking the global excellent result and evolution speed.The computer simula-tion results in a multi-dimension function optimization demonstrate that the proposed algorithms are superior to original particle swarm optimization algorithm.