摘要
粒子群算法是一种典型的智能优化算法,被广泛应用于各个领域,但算法本身也存在着在收敛后期容易陷入局部最优的缺陷,针对这一问题,借鉴免疫系统自我调节机制,引入浓度调节机制和免疫操作机制,提出一种基于免疫机理的粒子群算法,提高算法粒子群体的多样性,根据种群粒子亲和度和浓度群自适应调整搜索粒子的速度和方向,提高算法性能。将算法用于典型多峰函数极值求解,仿真结果表明,算法具有较好的全局收敛性和收敛精度,具有良好的优化性能。
This paper uses the immune system self-regulation mechanism,introduces the concentration regulation mechanism and the immune operation mechanism,and proposes a kind of exemption based on the immune system.The particle swarm optimization（PSO） of the epidemic mechanism improves the diversity of the particle swarm.It adaptively adjusts the velocity and direction of the particle according to the particle affinity and concentration group,and improves the performance of the algorithm.The algorithm is used to solve the extreme value of the typical multi peak function.
出处
《工业控制计算机》
2018年第10期113-115,共3页
Industrial Control Computer
关键词
粒子群算法
免疫操作
自适应搜索
多峰函数优化
particle swarm optimization
immune operation
adaptive search
multi peak function optimization
