含约束条件遗传算法在连续催化重整优化操作中的应用
Optimization of Continuous Catalytic Reforming Based on Genetic Algorithm with Constrains
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摘要: 介绍了通过惩罚函数法解决含约束条件遗传算法的实现问题。分别采用内点法和外点法,将有约束优化问题转化为无约束的优化问题,再利用Matlab编制遗传算法程序。通过对连续催化重整优化操作过程仿真计算,证明该方法具有快速收敛且优化结果好的特点。Abstract: Genetic algorithm (GA) is an effective method for searching the global optimal resoluation. This paper proposes the methods of using punishment function to realize GA with constrains, and then constructing GA program by Matlab tools. In the end, the modified GA is applied to optimize the parameters of continuous catalytic reforning. The results show that the algorithm can converge to good result rapidly. It demonstrates that GA is highly effective and has a good prospect.