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  多目标优化 相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题(Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle)