混沌粒子群算法在水污染控制系统规划中的应用
Chaotic particle swarm optimization for water pollution control system application
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摘要: 针对常用的最优化方法解决水污染控制系统规划问题运算过程较复杂，容易陷入局部极值，且优化解精度不高的情况，尝试利用混沌方法和粒子群算法相结合的混沌粒子群算法 (chaos particle swarm optimization，CPSO)求解此类问题。CPSO算法具有原理简单，且能快速获得最优解的特点。在实例应用中与遗传算法和MATLAB优化函数的优化结果做了比较，CPSO算法的性能以及得到的解明显优于后两种方法，验证了该方法的可行性和有效性。Abstract: As to common optimization methods to solve the planning issues of water pollution control system, the computational process is relatively complex, it is easy to fall into local optimum and the optimal solution is low precise. In order to improve these issues, this paper tried to use chaotic particle swarm optimization algorithm (CPSO) that was proposed by combining particle swarm optimization with chaos. CPSO had an advantage that was simple in principle and could quickly obtain the optimal solution. By comparing the solution of CPSO with genetic algorithm and MATLAB optimization function's in the practical application, the performance and solution of CPSO was proved better than the latter two. Meanwhile, the feasibility and effectiveness of CPSO were also verified.
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