An evolutionary approach to preference disaggregation in a MURAME-based credit scoring problem
AbstractIn this paper we use an evolutionary approach in order to infer the values of the parameters (weights of criteria, preference, indifference and veto thresholds) for developing the multicriteria method MURAME. According to the logic of preference disaggregation, the problem consists in finding the parameters that minimize the inconsistency between the model obtained with those parameters and that one connected with a given reference set of decisions revealed by the decision maker; in particular, two kinds of functions are considered in this analysis, representing a measure of the model inconsistency compared to the actual preferential system. In order to find a numerical solution of the mathematical programming problem involved, we adopt an evolutionary algorithm based on the Particle Swarm Optimization (PSO) method, which is an iterative heuristics grounded on swarm intelligence. The proposed approach is finally applied to a creditworthiness evaluation problem in order to test the methodology on a real data set provided by an Italian bank.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Department of Management, Università Ca' Foscari Venezia in its series Working Papers with number 5.
Length: 21 pages
Date of creation: Apr 2012
Date of revision:
Preference disaggregation; Murame; Particle swarm optimization;
Find related papers by JEL classification:
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- G2 - Financial Economics - - Financial Institutions and Services
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jacquet-Lagreze, Eric & Siskos, Yannis, 2001. "Preference disaggregation: 20 years of MCDA experience," European Journal of Operational Research, Elsevier, vol. 130(2), pages 233-245, April.
- Nikos S. Thomaidis & Timotheos Angelidis & Vassilios Vassiliadis & Georgios Dounias, 2009.
"Active Portfolio Management With Cardinality Constraints: An Application Of Particle Swarm Optimization,"
New Mathematics and Natural Computation (NMNC),
World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 535-555.
- Nikos Thomaidis & Timotheos Angelidis & Vassilios Vassiliadis & Georgios Dounias, 2008. "Active Portfolio Management With Cardinality Constraints: An Application Of Particle Swarm Optimization," Working Papers 0016, University of Peloponnese, Department of Economics.
- Willard I. Zangwill, 1967. "Non-Linear Programming Via Penalty Functions," Management Science, INFORMS, vol. 13(5), pages 344-358, January.
- Marco Corazza & Stefania Funari & Federico Siviero, 2008. "An MCDA-based Approach for Creditworthiness Assessment," Working Papers 177, Department of Applied Mathematics, Università Ca' Foscari Venezia.
- Doumpos, Michael & Zopounidis, Constantin, 2011. "Preference disaggregation and statistical learning for multicriteria decision support: A review," European Journal of Operational Research, Elsevier, vol. 209(3), pages 203-214, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marco LiCalzi).
If references are entirely missing, you can add them using this form.