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对比了进化算法(基因算法)与确定性算法(共轭梯度法)在优化控制问题中的优化效率。两种方法都与分散式优化策略-Nash对策进行了结合,并成功地应用于优化控制问题。计算模型采用绕NACA0012翼型的位流流场。区域分裂技术的引用使得全局流场被分裂为多个带有重叠区的子流场,使用4种不同的方法进行当地流场解的耦合,这些算法可以通过当地的流场解求得全局流场解。数值计算结果的对比表明,进化算法可以得到与共轭梯度法相同的计算结果,并且进化算法的不依赖梯度信息的特性使其在复杂问题及非线性问题中具有广泛的应用前景。
The optimization efficiency of the optimization control problem is compared between evolutionary algorithm (genetic algorithm) and deterministic algorithm (conjugate gradient method). Both methods are combined with the decentralized optimization strategy-Nash strategy and applied successfully to the optimization control problem. The computational model uses a bitflow field around the NACA0012 airfoil. The introduction of the regional splitting technique makes the global flow field split into multiple sub-flow fields with overlapping regions. Four different methods are used to couple local flow solutions. These algorithms can obtain the global flow through local flow field solutions Field solution. The comparison of the numerical results shows that the evolutionary algorithm can get the same result as the conjugate gradient method, and the evolutionary algorithm does not depend on the characteristics of gradient information to make it have a wide range of applications in complex and nonlinear problems.