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Journal Articles Annals of Mathematics and Artificial Intelligence Year : 2016

Portfolio Approaches for Constraint Optimization Problems

Abstract

Within the Constraint Satisfaction Problems (CSP) context, a methodology that has proven to be particularly performant consists of using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations have been done in the world of Constraint Optimization Problems (COP). In this work, we provide a generalization to COP as well as an empirical evaluation of different state of the art existing CSP portfolio approaches properly adapted to deal with COP. The results obtained by measuring several evaluation metrics confirm the effectiveness of portfolios even in the optimization field, and could give rise to some interesting future research.
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Dates and versions

hal-01336686 , version 1 (23-06-2016)

Identifiers

  • HAL Id : hal-01336686 , version 1

Cite

Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro. Portfolio Approaches for Constraint Optimization Problems. Annals of Mathematics and Artificial Intelligence, 2016. ⟨hal-01336686⟩
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