拟可微规划的约束规范和对偶问题

在经典非线性规划中，导出最优性条件的一般方法是，在给定的可行点处通过对函数的一阶逼近，将一个非线性规划问题线性化为一个线性规划问题。可微非线性规划问题的线性化过程可以自然地推广到拟可微的情形。正如在经典情况中那样，为了确保在原问题的局部极小值点处，零向量是相应的“拟线性化”问题的最优解，必须对原问题的约束函数施加所谓的约束规范。本考虑了形如min{f(x)|g（x)≤0}的不等式约束拟可微规划问题的约束规范，这里f和g是Demyanov意义下的拟可微函数。中介绍了各种约束规范，提出了一个新的约束规范，研究了这些条件之间的关系，并且引入了一个Wolf对偶问题，给出了相应的对偶定理。

CONSTRAINT QUALIFICATIONS AND DUAL PROBLEMS FOR QUASI-DIFFERENTIABLE PROGRAMMING

In classical nonlinear programming, it is a general method of developing optimality conditions that a nonlinear programming problem is linearized as a linear programming problem by using first order approximations of the functions at a given feasible point. The linearized procedure for differentiable nonlinear programming problems can be naturally generalized to the quasi-differential case. As in classical case so-called constraint qualifications have to be imposed on the constraint functions to guarantee that for a given local minimizer of the original problem the nullvector is an optimal solution of the corresponding "quasilinearized" problem. In this paper, constraint qualifications for inequality constrained quasi-differentiable programming problems of type min{f(x)|g(x)≤0} are considered, where f and g are qusidifferentiable functions in the sense of Demyanov. Various constraint qualifications for this problem are presented and a new one is proposed. The relations among these conditions are investigated. Moreover, a Wolf dual problem for this problem is introduced, and the corresponding dual theorems are given.