We discuss necessary conditions (with less Lagrange multipliers), perturbations and general algorithms in non convex optimization problems. Optimal control problems with mixed constraints, governed by ordinary differential equations, are also studied in this context. Our treatment is based on a recent approach to implicit systems, constructing parametrizations of the corresponding manifold, via iterated Hamiltonian equations.

中文翻译：

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隐式参数化及其在优化和控制中的应用

我们讨论非凸优化问题中的必要条件（具有较少的Lagrange乘数），扰动和一般算法。在这种情况下，还研究了由常微分方程控制的具有混合约束的最优控制问题。我们的处理基于对隐式系统的最新方法，该方法通过迭代的哈密顿方程构造相应流形的参数化。