Approximating incompletely defined utility functions of qualitative multi-criteria modeling method DEX

Approximating incompletely defined utility functions of qualitative multi-criteria modeling... Decision analysis is aimed at supporting people who make decisions in order to satisfy their needs and objectives. The method called DEX is a qualitative multi-criteria decision analysis approach that provides support to decision makers in evaluating and choosing decision alternatives by using discrete attributes and rule-based utility functions. In this work, we extend our previous efforts of approximating complete, monotone DEX utility functions with methods Direct marginals, UTADIS and Conjoint analysis to incompletely defined utility functions. The experiments are performed both on functions obtained by solving real world decision making problems and on artificially created ones. The results show that all three methods provide accurate approximations of incompletely defined DEX utility functions, when the evaluation is done only on rules present in these incompletely defined functions. Among the three methods, the Conjoint analysis method generally has the best performance, however it is closely followed by the Direct marginals method. The Conjoint analysis method also achieves a better performance in approximating fully defined DEX utility functions by using incompletely defined instances of those functions. The UTADIS method performs comparatively well with functions having a high percentage of missing values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Central European Journal of Operations Research Springer Journals

Approximating incompletely defined utility functions of qualitative multi-criteria modeling method DEX

Loading next page...
 
/lp/springer_journal/approximating-incompletely-defined-utility-functions-of-qualitative-qCdp9e79WH
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Business and Management; Operations Research/Decision Theory
ISSN
1435-246X
eISSN
1613-9178
D.O.I.
10.1007/s10100-016-0451-x
Publisher site
See Article on Publisher Site

Abstract

Decision analysis is aimed at supporting people who make decisions in order to satisfy their needs and objectives. The method called DEX is a qualitative multi-criteria decision analysis approach that provides support to decision makers in evaluating and choosing decision alternatives by using discrete attributes and rule-based utility functions. In this work, we extend our previous efforts of approximating complete, monotone DEX utility functions with methods Direct marginals, UTADIS and Conjoint analysis to incompletely defined utility functions. The experiments are performed both on functions obtained by solving real world decision making problems and on artificially created ones. The results show that all three methods provide accurate approximations of incompletely defined DEX utility functions, when the evaluation is done only on rules present in these incompletely defined functions. Among the three methods, the Conjoint analysis method generally has the best performance, however it is closely followed by the Direct marginals method. The Conjoint analysis method also achieves a better performance in approximating fully defined DEX utility functions by using incompletely defined instances of those functions. The UTADIS method performs comparatively well with functions having a high percentage of missing values.

Journal

Central European Journal of Operations ResearchSpringer Journals

Published: Aug 2, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off