使用粒子群算法解决优化问题，该算法有全局搜索和局部搜索能力，方便快捷。-Particle swarm algorithm to solve the optimization problem, the algorithm global search and local search capability, quick and easy.

Shu－ChuanChu受到猫日常行为动作的启发，于2006年提出了猫群算法。猫群算法的最大特征表现为在进化过程中能够同时进行局部搜索和全局搜索，具有很好的收敛速度-Shu- ChuanChu inspired by cats everyday actions, cat swarm algorithm is proposed in 2006. Cat swarm algorithm of the biggest characteristic is in the process of evolut

序列比对中的smith-waterman算法，应用于局部序列比对，寻找最优化比对序列，精确度高-Smith- waterman in sequence alignment algorithm, is applied to the local sequence alignment, search for optimal matching sequence, high precision

Recently more research works are focused on multi-objective particle swarm optimization algorithm (MOPSO) due to its ability of global and local search for solving multi-objective optimization problems (MOOPs) however, most of existing MOPSOs can