This works investigates a conceptual algorithm for computing critical points of nonsmooth nonconvex optimization problems whose objective function is the sum of two locally Lipschitzian (component) functions. We show that upon additional assumptions on the component functions and or feasible set, the given algorithm extends several well-known optimization methods.

中文翻译：

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最小化局部Lipschitzian函数之和的一些简要观察

这项工作研究了一种概念算法，用于计算非光滑非凸优化问题的关键点，其目标函数是两个局部Lipschitzian（分量）函数之和。我们证明，在对组件函数和或可行集进行其他假设时，给定算法扩展了几种众所周知的优化方法。