1·Aiming at the optimization problem in engineering, this paper proposes a new algorithm for con-strained optimization problem by combining PSO with death penalty.
针对工程中的优化问题，将粒子群算法与死亡罚函数法相结合，提出一种求解有约束问题的优化算法。
2·And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
3·PSO has been proved to be an effective global optimization algorithm. It is easy to implement, quickly convergence, and has been successfully applied to many engineering fields.
粒子群算法已经被证明是一种有效的全局优化算法，其收敛速度快，易于实现，已经成功地运用到了许多工程领域。
4·We also propose to use a hybrid version of PSO embedding a local optimizer to enhance the performance.
我们也建议用混合版本的粒子群算法嵌入局部优化，提高了性能。
5·PSO receives widespread attention of many scholars, and has been applied to many practical engineering.
粒子群算法受到很多研究学者的关注，并被应用到很多实际工程领域。