Interactive and nonparametric modeling of preferences on an ordinal scale using small data

Date

2016-12-15

Author

Erişkin, Levent
Köksal, Gülser

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

210
views

0
downloads

In this study, we consider learning preference structure of a Decision Maker (DM). Many preference modeling problems in a variety of fields such as marketing, quality control and economics involve possibly interacting criteria, and an ordinal scale is used to express preference of objects. In these cases, typically underlying preference structure of the DM and distribution of criteria values are not known, and only a few data can be collected about the preferences of the DM.

Subject Keywords

Preference modeling, Sorting, Active learning, Interactive approach, Multi criteria decision aid

URI

https://hdl.handle.net/11511/40164

Journal

EXPERT SYSTEMS WITH APPLICATIONS

DOI

https://doi.org/10.1016/j.eswa.2016.08.063

Collections

Department of Industrial Engineering, Article

Suggestions

OpenMETU
Core

Interactive and nonparametric modeling of preferences on an ordinal scale using small data Erişkin, Levent; Köksal, Gülser; Department of Industrial Engineering (2014) In this study, we consider learning preference structure of a Decision Maker (DM). Many preference modeling problems in a variety of fields such as marketing, quality control and economics, involve possibly interacting criteria, and an ordinal scale is used to express preference of objects. In these cases, typically underlying preference structure of the DM and distribution of criteria values are not known, and only a few data can be collected about the preferences of the DM. For developing a preference mod...
Interactive approaches for biobjective problems with progressively changing solution sets Karakaya, Gülşah (Wiley, 2021-01-01) In this study, we develop interactive approaches to find a satisfactory alternative of a decision maker (DM) having a quasiconvex preference function where the alternative set changes progressively. In this environment, we keep searching the available set of alternatives and estimating the preference function of the DM. As new alternatives emerge, we make better use of the available preference information and eventually converge to a preferred alternative of the DM. We test our approaches on biobjective, mu...
Interactive Approaches to Multiple Criteria Sorting Problems: Entropy-Based Question Selection Methods Özarslan, Ali; Karakaya, Gülşah (2022-08-01) In this study, interactive approaches for sorting alternatives evaluated on multiple criteria are developed. The possible category ranges of alternatives are defined by mathematical models iteratively under the assumption that the preferences of the decision maker (DM) are consistent with an additive utility function. Simulation-based and model-based parameter generation methods are proposed to hypothetically assign the alternatives to categories. A practical approach to solve the incompatibility problem of...
An Interactive partitioning approach for multiobjective decision making under a general monotone utility function Karasakal, Esra (2013-09-01) We develop an interactive partitioning approach for solving the multiobjective decision making problem of a decision maker (DM) who has an implicit general monotone utility function. The approach reduces feasible solution space using the DM's preferences. Hypothetical solutions called partition ideals (PIs) that dominate portions of the efficient frontier are generated and those that are inferior to a feasible solution are used to eliminate the dominated regions. We investigate the issues in representation ...
Evolving a hierarchical decision making mechanism using fuzzy logic Beldek, Ulas; Leblebicioğlu, Mehmet Kemal (2008-12-01) In this study, a new hierarchical decision-making and decision-fusion mechanism is introduced for solving decision making problems in a consistent manner. This mechanism is constructed by using a genetic algorithm. The proposed mechanism employs fuzzy logic and a performance index determined based on the performance of decision-making agents at successive hierarchical levels. The mechanism is such that the decisions in previous levels are influential on the current level decisions according to the performan...

Citation Formats

L. Erişkin and G. Köksal, “Interactive and nonparametric modeling of preferences on an ordinal scale using small data,” EXPERT SYSTEMS WITH APPLICATIONS, pp. 345–360, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40164.