Inducing probability distributions on the set of value functions by Subjective Stochastic Ordinal Regression

Highlights：

• Multiple criteria ranking problem is approached using Subjective Stochastic Ordinal Regression (SSOR).

• Preferences of the decision maker are expressed through pairwise comparisons of some reference alternatives.

• A part of pairwise comparisons is certain, and another part is uncertain.

• Uncertain pairwise comparisons are used to build a probability distribution over the space of all preference models compatible with certain pairwise comparisons.

• From sampling of this distribution, one learns a probability with which a is ranked on the rth position (rank acceptability index), and probability that a is preferred to b (pairwise winning index).

摘要

•Multiple criteria ranking problem is approached using Subjective Stochastic Ordinal Regression (SSOR).•Preferences of the decision maker are expressed through pairwise comparisons of some reference alternatives.•A part of pairwise comparisons is certain, and another part is uncertain.•Uncertain pairwise comparisons are used to build a probability distribution over the space of all preference models compatible with certain pairwise comparisons.•From sampling of this distribution, one learns a probability with which a is ranked on the rth position (rank acceptability index), and probability that a is preferred to b (pairwise winning index).

论文关键词：Multiple criteria decision aiding,Ordinal regression,Stochastic multiobjective acceptability analysis,Multi-attribute value function,Uncertain preference information,Probability distribution

论文评审过程：Received 1 May 2016, Revised 3 August 2016, Accepted 28 August 2016, Available online 29 August 2016, Version of Record 4 October 2016.