集值映射向量最优化中的拉格朗日对偶问题

Lagrangian duality for vector optimization of set-valued maps

引入集值映射向量最优化问题的最小解的广义拉格朗日最优条件和闭包类凸假设下通常的拉格朗日最优条件。利用这些结果和象正则条件假设,得到较弱条件下最小问题的拉格朗日对偶定理。

It introduces a generalized Lagrangian optimality condition for a minimal solution of vector optimization of set-valued maps and some lagrangian multiplier theorems under closure convexlike asssumption. By applying these results and the image regularity condition, the Lagrangian duality for minimality is presented under a weaker asssumption.