A Subgradient-Like Algorithm for Solving Vector Convex Inequalities
A Subgradient-Like Algorithm for Solving Vector Convex Inequalities
复制标题
求解向量凸不等式的类次梯度算法
DOI：
10.1007/s10957-013-0300-1
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
L. R. L. Pérez
中科院分区：
文献类型：
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作者：
Yunier Bello Cruz;L. R. L. Pérez
本文给出了求解Hilbert空间中向量凸不等式组的罗宾逊次梯度算法的一个强收敛变形。所提出的方法的优点是，它的收敛性强，当问题的解决方案，在温和的假设。该算法还具有以下理想的性质：序列收敛到问题的解决方案，这是最接近的起点，并完全保持在三个球的交集半径小于初始距离的解决方案集。
In this paper, we propose a strongly convergent variant of Robinson's subgradient algorithm for solving a system of vector convex inequalities in Hilbert spaces. The advantage of the proposed method is that it converges strongly, when the problem has solutions, under mild assumptions. The proposed algorithm also has the following desirable property: the sequence converges to the solution of the problem, which lies closest to the starting point and remains entirely in the intersection of three balls with radius less than the initial distance to the solution set.