In this paper we study a broad class of structured nonlinear programming (SNLP) problems. In particular, we first establish the first-order optimality conditions for them. Then we propose sequential convex programming (SCP) methods for solving them in which each iteration is obtained by solving a convex programming problem. Under some suitable assumptions, we establish that any accumulation point of the sequence generated by the methods is a KKT point of the SNLP problems. In addition, we propose a variant of the SCP method for SNLP in which nonmonotone scheme and ``local'' Lipschitz constants of the associated functions are used. A similar convergence result as mentioned above is established.
翻译：在本文中,我们研究了一系列广泛的结构化非线性编程问题,特别是,我们首先为它们确定第一级的最佳性条件,然后提出分流编程(SCP)方法,以解决通过解决分流编程问题获得每种迭代的方法。根据一些适当的假设,我们确定这些方法产生的序列的累积点是SNLP问题的一个KKT点。此外,我们提出了SCP方法的变式,即使用非模子制和“当地”相关函数的“利普施奇茨常数”的SNLP方法,并确定了上述类似的趋同结果。
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