Interactive portfolio selection involving multicriteria sorting models

Ali Tlili (), Oumaima Khaled (), Vincent Mousseau () and Wassila Ouerdane ()
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Ali Tlili: Université Paris-Saclay
Oumaima Khaled: Université Paris-Saclay
Vincent Mousseau: Université Paris-Saclay
Wassila Ouerdane: Université Paris-Saclay

Annals of Operations Research, 2023, vol. 325, issue 2, No 17, 1169-1195

Abstract: Abstract Given a set of items, the portfolio selection problem involves selecting a subset of the items subject to resource constraints. We propose in this paper a multiobjective interactive approach based on a constrained Non-Compensatory Sorting model which integrates preferences both on items and portfolios in the same device. More precisely, we combine two evaluations models. The first one assigns items into two categories ( Good / Bad ) and model resource limitation using weighted cardinality constraints in such a way that the portfolio is composed of the items assigned to the good category. The second evaluation level compares portfolios on a set of portfolio-related criteria. We learn the constrained sorting model, based on a learning set, with SAT/MaxSAT language, which proves to be efficient for the preference learning task.

Keywords: Portfolio selection; Multicriteria decision; Non-compensatory sorting; Preference learning; SAT/MaxSAT (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-022-04877-z

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