数据包络分析中的特征选择：一种数学Optimization方法
Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach
摘要：
本文提出了一种数据包络分析（DEA）中特征（输入和输出）选择的综合方法。该DEA模型是丰富的零-一决策变量建模的选择功能，产生一个混合的线性规划线性规划制定。这种单模型方法可以处理不同的目标函数以及约束，以结合来自真实世界应用的期望属性。我们的方法是说明对电力配电系统运营商（DSO）的基准。数值结果突出了我们的单模型方法提供给用户的优势，在选择功能的数量，以及建模的成本和它们的性质。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
