Abstract
In this paper we deal with the problem of preference disaggregation in credit scoring problems developed by using multicriteria analysis. In order to determine the values of the parameters that characterize the preference model of the decision maker, we adopt Particle Swarm Optimization, which is a biologically-inspired heuristics based on swarm intelligence. We test the ability of PSO to find the optimal values of the parameters on a real data set provided by an Italian bank.
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Notes
- 1.
For more details about the nature of input data, we refer to Sect. 4.
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Corazza, M., Funari, S., Gusso, R. (2014). Particle Swarm Optimization for Preference Disaggregation in Multicriteria Credit Scoring Problems. In: Corazza, M., Pizzi, C. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-02499-8_11
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DOI: https://doi.org/10.1007/978-3-319-02499-8_11
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