论文标题
DC约束数学编程问题中的最佳条件
Optimality conditions in DC constrained mathematical programming problems
论文作者
论文摘要
本文为在新的资格条件下的本地凸空间中抽象约束数学编程问题提供了必要和足够的最佳条件。我们的方法利用了某些映射的几何特性，尤其是它们作为凸函数差异的结构，并使用了广义分化的技术（细分和代码分离）。事实证明，这些工具可以从阿斯普伦德空间的范围中有效地使用。在无限，随机和半准编程中的应用是在单独的部分中开发的。
This paper provides necessary and sufficient optimality conditions for abstract constrained mathematical programming problems in locally convex spaces under new qualification conditions. Our approach exploits the geometrical properties of certain mappings, in particular their structure as difference of convex functions, and uses techniques of generalized differentiation (subdifferential and coderivative). It turns out that these tools can be used fruitfully out of the scope of Asplund spaces. Applications to infinite, stochastic and semi-definite programming are developed in separate sections.
