动态离散粒子群优化算法

为解决现实世界中动态环境下的离散事件优化问题,研究了当前已被广泛应用于动态环境或离散运算优化问题的粒子群优化算法(PSO),据此提出了一种动态离散PSO算法.该算法设计了一种环境绝对值和环境敏感性判定策略来实现动态环境的监测与响应,并通过带变异算子的离散PSO算法公式的重新定义来满足大规模离散运算需求.最后,利用离散时间系统的零状态响应求解评价了该算法的性能,结果表明,该算法在定义域内具有较好的收敛性.

Optimization algorithm of dynamic discrete particle swarm

To solve the optimization problems of discrete events under dynamic environment in the real world, particle swarm optimization (PSO) algorithm is studied, which is used widely to solve the optimization problems in the dynamic environment or discrete operation at present, and a dynamic discrete PSO algorithm is proposed. The dynamic environment is monitored and responsed with a judgement strategy of the environment absolute value and sensitivity in this algorithm, and redefined the formals of discrete PSO algorithm with mutation operator, the proposed algorithm could satisfy the demand of large-scale discrete computing. Finally, this algorithm is evaluated by using the solving of zero state response in discrete-time systems, which results shows that this algorithm has a good convergence in the domain of definition.