Constrained optimization using the chaotic Lagrangian method and the simultaneous perturbation gradient approximation
Constrained optimization using the chaotic Lagrangian method and the simultaneous perturbation gradient approximation
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发表时间：
2009-11
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通讯作者：
T. Okamoto;H. Hirata
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作者：
T. Okamoto;H. Hirata
作为求解约束优化问题的全局优化方法之一，我们提出了一种混沌拉格朗日方法，该方法利用混沌搜索轨迹产生于一个关于增广拉格朗日量的耦合梯度动力学。我们已经证实了混沌拉格朗日方法的全局搜索能力。然而，混沌拉格朗日方法不能应用于一类目标函数不可微的问题，因为混沌拉格朗日方法使用梯度作为驱动力。在本研究中，我们将同时微扰梯度近似引入混沌拉格朗日方法，以近似计算梯度。
As one of the global optimization methods to solve constrained optimization problems, we have proposed a chaotic Lagrangian method which utilizes chaotic search trajectories generated in a coupled gradient dynamics with respect to the augmented Lagrangian. We have confirmed the global search capability of the chaotic Lagrangian method. However, the chaotic Lagrangian method cannot be applied to a class of problems whose objective function is indifferentiable, because the chaotic Lagrangian method uses the gradient as a driving force. In this study, we introduce the simultaneous perturbation gradient approximation into the chaotic Lagrangian method in order to compute the gradient approximately.