Road to robust prediction of choices in deterministic MCDM

作     者：Pajala, Tommi Korhonen, Pekka Wallenius, Jyrki 

作者机构：Aalto Univ Sch Business Dept Informat & Serv Econ POB 21220 Aalto 00076 Finland 

出 版 物：《EUROPEAN JOURNAL OF OPERATIONAL RESEARCH》 (欧洲运筹学杂志)

年 卷 期：2017年第259卷第1期

页      面：229-235页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Academy of Finland KAUTE Foundation 

主　　题：Multi objective programming Preference prediction Multiple criteria decision making Linear value function Bayesian model 

摘      要：We compare five different prediction methods (linear estimated weights, AHP weights, equal weights, logistic regression, and a lexicographic method) in their success rate for predicting preferences in pairwise choices. Students were asked to make pairwise comparisons between student apartments on four criteria: size, rent, travel time to the university and travel time to a (hobby) location of their choice. First ten choices were used to set up the estimation model, and subsequent ten choices are used for prediction. We find that the linear estimation method has the highest prediction success rate. Furthermore, the probability of predicting a choice correctly differs only slightly (by 0.1) between linear consistent and inconsistent subjects, ie. subjects whose preferences were consistent or inconsistent with a linear value function. This shows that in the absence of other preference information, a linear value function is suitable for prediction purposes. (C) 2016 Elsevier B.V. All rights reserved.