论文标题
用于有限的凸矢量优化问题的benson型算法与顶点选择
A Benson-Type Algorithm for Bounded Convex Vector Optimization Problems with Vertex Selection
论文作者
论文摘要
我们提出了一种算法，用于求解有限的凸矢量优化问题。该算法既提供了上图像的外部和内部多面体近似值。这是对Löhne，Rudloff和Ulus在2014年提出的原始算法的修改。在那里，已知的外部近似的顶点被依次切断以改善近似误差。我们提出了一项新的高效选择规则，以决定要切断哪个顶点。提供了数值示例，这些示例说明了该方法可以整体上解决标量问题的较少，因此在达到相同的近似质量的同时可能会更快。
We present an algorithm for approximately solving bounded convex vector optimization problems. The algorithm provides both an outer and an inner polyhedral approximation of the upper image. It is a modification of the primal algorithm presented by Löhne, Rudloff, and Ulus in 2014. There, vertices of an already known outer approximation are successively cut off to improve the approximation error. We propose a new and efficient selection rule for deciding which vertex to cut off. Numerical examples are provided which illustrate that this method may solve fewer scalar problems overall and therefore may be faster while achieving the same approximation quality.
