论文标题
数据包络分析中的特征选择：一种数学优化方法
Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach
论文作者
论文摘要
本文提出了在数据包络分析（DEA）中的特征（输入和输出）选择的集成方法。 DEA模型富含零一个决策变量，以建模特征的选择，从而产生混合整数线性编程公式。这种单模方法可以处理不同的目标功能以及约束，以合并现实世界应用程序中理想的属性。我们的方法是关于电力分配系统运营商（DSO）的基准测试的。数值结果强调了我们的单模方法为用户提供的优势，即选择功能数量以及对其成本和性质进行建模。
This paper proposes an integrative approach to feature (input and output) selection in Data Envelopment Analysis (DEA). The DEA model is enriched with zero-one decision variables modelling the selection of features, yielding a Mixed Integer Linear Programming formulation. This single-model approach can handle different objective functions as well as constraints to incorporate desirable properties from the real-world application. Our approach is illustrated on the benchmarking of electricity Distribution System Operators (DSOs). The numerical results highlight the advantages of our single-model approach provide to the user, in terms of making the choice of the number of features, as well as modeling their costs and their nature.
