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中文摘要：
针对粒子群算法在寻优中存在早熟和收敛精度不高等问题，论文对粒子位置的更新策略以及更新公式进行改进，提出了一种新的简化粒子群优化算法（NewSimpleParticleSwarmOptimiza-tion，NsPso），并将其在15个多极值基准函数进行全局最优化测试，实验结果表明，NSPSO算法收敛的精度大大提高了，而且算法收敛速度也很快，对于高、低维复杂函数的优化均适用．
英文摘要：
Concerning the problems of premature and low convergence accuracy for the particle？ swarm？algorithm in search of optimization, update strategy and formula of the particle position have been made improvements in this paper, and a new simple particle swarm optimization （NSPSO） is proposed. Through global optimization tests in 15 multiple maximum benchmark functions, the experimental results show the convergence accuracy of NSPSO has improved greatly and the rate of convergence become faster, which can be applied in the optimization for high and low dimensional complicated functions.
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