【摘要】 约束拟可微优化的Lagrange乘子型最优性条件,往往与某些特殊对象(超梯度,方向)的选取有关,这是拟可微优化的核心问题之一.应用凸紧集与次线性函数的Minkowski对偶,利用次线性泛函产生的非线性Lagrange函数,对于具有有限个等式和不等式约束的拟可微优化,给出了一个与特殊对象选取无关的次线性的Lagrange乘子法则,推广了已有的结果.更多还原

【Abstract】 Lagrange muliplier type optimality conditions for constrained quasidifferentiable programming usually depend on the choice of special objects(super-gradient,direction,and so on),which is one of the key problems for constrained quasidifferentiable programming.In this paper,applying Minkowski duality of convex compact sets and sublinear functions,the sublinear Lagrange multiplic rule for quasidifferentiable optimization with a finite number of inequality and equality constraints are deduced by the nonlinear Lagrange function generated by a sublinear function,which improves the existing results.更多还原