Unbiased approximation in multicriteria optimization
Unbiased approximation in multicriteria optimization
复制标题
多标准优化中的无偏近似
DOI：
10.1007/s001860200217
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发表时间：
2003
影响因子：
1.2
通讯作者：
M. Wiecek
中科院分区：
文献类型：
--
作者：
K. Klamroth;J. Tind;M. Wiecek
给出了一般、凸和非凸多准则规划的非支配集分段线性逼近算法。利用多面体距离函数构造近似并评价其质量。函数自动适应问题的结构和尺度，使逼近过程无偏和自驱动。决策者的偏好，如果有的话，可以很容易地纳入，但不是程序所要求的。
Algorithms generating piecewise linear approximations of the nondominated set for general, convex and nonconvex, multicriteria programs are developed. Polyhedral distance functions are used to construct the approximation and evaluate its quality. The functions automatically adapt to the problem structure and scaling which makes the approximation process unbiased and self-driven. Decision makers preferences, if available, can be easily incorporated but are not required by the procedure.