中文摘要：

针对粒子群优化算法在整个迭代过程中粒子极易陷于局部极值区域，提出一种混沌动态粒子数的粒子群优化算法，也即在判定全局最优值处于停滞时，以混沌策略对粒子进行位置初始化后加入种群，从而有效地保证了粒子群的多样性。用4个测试函数验证了该算法具有很好的寻优能力和较高的搜索精度。

英文摘要：

For the particle swarm optimization,the particles are easily trapped in the local extremum region in the whole iterative process.This paper proposes a particle swarm optimization based on chaotic dynamic population size.When the global optimum is judged in stagnation,the location of particles are initialized using the chaotic strategy,then be added to the popu- lation, thus can effectively ensure the diversity of the particle swarm.Four test functions verify that the algorithm has very good optimizing ability and high precision of the search.