We present the second-order point-based (necessary and sufficient) optimality conditions for nonlinear programming with continuously differentiable data, via the regular and limiting (Mordukhovich) second-order subdifferentials. The sharper results are obtained for \(C^{1,1}\) data. Also, we derive a second-order characterization for (strictly and strongly) pseudoconvex, continuously differentiable functions.

中文翻译：

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具有 $$C^1$$ C 1 数据的约束优化问题的二阶最优性条件通过正则和限制次微分

我们通过规则和限制（Mor​​dukhovich）二阶次微分，为具有连续可微数据的非线性规划提出了基于二阶点的（必要和充分）最优性条件。\(C^{1,1}\)数据获得了更清晰的结果。此外，我们推导出（严格和强）赝凸连续可微函数的二阶特征。