DOI
10.9781/ijimai.2016.3712
Abstract
In the context of Constraint Programming, a portfolio approach exploits the complementary strengths of a portfolio of different constraint solvers. The goal is to predict and run the best solver(s) of the portfolio for solving a new, unseen problem. In this work we reproduce, simulate, and evaluate the performance of different portfolio approaches on extensive benchmarks of Constraint Satisfaction Problems. Empirical results clearly show the benefits of portfolio solvers in terms of both solved instances and solving time.
Source Publication
International Journal of Interactive Multimedia and Artificial Intelligence
Recommended Citation
Amadini, Roberto; Mauro, Jacopo; and Gabbrielli, Maurizio
(2016)
"An Extensive Evaluation of Portfolio Approaches for Constraint Satisfaction Problems,"
International Journal of Interactive Multimedia and Artificial Intelligence: Vol. 3:
Iss.
7, Article 2.
DOI: 10.9781/ijimai.2016.3712
Available at:
https://ijimai.researchcommons.org/ijimai/vol3/iss7/2
