线性递减权重粒子群优化算法是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。 -Linear decreasing weight particle swarm optimization starting from random solutions to find the optimal solution by iteration, it is also the fitness to evaluate the quality of the solution, but it is much simpler than the genetic algorithm rules, it is not a genetic algorithm " cross"　(Crossover) and " variation"　(Mutation) operation, which follow the current search for the optimal value to find the global optimum. The advantage of this algorithm is its ease of implementation, high accuracy, fast convergence and attracted the attention of the academic community, and demonstrated its superiority in solving practical problems.