Higher-order generalized convexity and duality in nondifferentiable multiobjective mathematical programming ✩
Higher-order generalized convexity and duality in nondifferentiable multiobjective mathematical programming ✩
复制标题
DOI：
10.1016/j.jmaa.2004.03.036
复制
发表时间：
2004-09
影响因子：
1.3
通讯作者：
Xinmin Yang;K. Teo;Xiaoqi Yang
中科院分区：
文献类型：
--
作者：
Xinmin Yang;K. Teo;Xiaoqi Yang
本文引入了一类广义凸性，描述了不可微多目标规划的统一高阶对偶模型，其中目标函数的每个分量都包含一个涉及紧凸集的支撑函数的项。在广义凸性条件下建立了弱对偶定理。从我们的结果可以很容易地推导出半正定二次型的平方根形式的支持函数的著名情况和其他特殊情况。
In this paper, a class of generalized convexity is introduced and a unified higher-order dual model for nondifferentiable multiobjective programs is described, where every component of the objective function contains a term involving the support function of a compact convex set. Weak duality theorems are established under generalized convexity conditions. The well-known case of the support function in the form of square root of a positive semidefinite quadratic form and other special cases can be readily derived from our results.