Compromise programming: Non-interactive calibration of utility-based metrics
Compromise programming: Non-interactive calibration of utility-based metrics
复制标题
妥协编程：基于实用程序的指标的非交互式校准
DOI：
10.1016/j.ejor.2015.01.031
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
G. Claassen
中科院分区：
文献类型：
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作者：
A. Kanellopoulos;J. C. Gerdessen;G. Claassen
效用函数已被广泛用于支持多目标决策。围绕理想结果扩展一般加性效用函数会产生折衷编程问题的复合线性二次度量。确定复合线性二次度量的未知参数需要与决策者进行大量交互，而决策者可能并不总是有空或有能力参与这一过程。我们提出了一种非交互式方法，该方法使用观察到的属性级别的信息来获取复合线性二次度量的未知参数，并实现预测和场景分析。该方法通过小规模数值示例进行说明。
Utility functions have been used widely to support multi-objective decision-making. Expansion of a general additive utility function around the ideal results in a composite linear-quadratic metric of a compromise programming problem. Determining the unknown parameters of the composite linear-quadratic metric requires substantial interaction with the decision maker who might not always be available or capable to participate in such a process. We propose a non-interactive method that uses information on observed attribute levels to obtain the unknown parameters of the composite linear-quadratic metric and enables forecasting and scenario analysis. The method is illustrated with a small scale numerical example.