TY - GEN
T1 - An empirical evaluation of portfolios approaches for solving CSPs
AU - Amadini, Roberto
AU - Gabbrielli, Maurizio
AU - Mauro, Jacopo
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Recent research in areas such as SAT solving and Integer Linear Programming has shown that the performances of a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. We report an empirical evaluation and comparison of portfolio approaches applied to Constraint Satisfaction Problems (CSPs). We compared models developed on top of off-theshelf machine learning algorithms with respect to approaches used in the SAT field and adapted for CSPs, considering different portfolio sizes and using as evaluation metrics the number of solved problems and the time taken to solve them. Results indicate that the best SAT approaches have top performances also in the CSP field and are slightly more competitive than simple models built on top of classification algorithms.
AB - Recent research in areas such as SAT solving and Integer Linear Programming has shown that the performances of a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. We report an empirical evaluation and comparison of portfolio approaches applied to Constraint Satisfaction Problems (CSPs). We compared models developed on top of off-theshelf machine learning algorithms with respect to approaches used in the SAT field and adapted for CSPs, considering different portfolio sizes and using as evaluation metrics the number of solved problems and the time taken to solve them. Results indicate that the best SAT approaches have top performances also in the CSP field and are slightly more competitive than simple models built on top of classification algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84879978727&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38171-3_21
DO - 10.1007/978-3-642-38171-3_21
M3 - Article in proceedings
AN - SCOPUS:84879978727
SN - 9783642381706
T3 - Lecture Notes in Computer Science
SP - 316
EP - 324
BT - Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems - 10th International Conference, CPAIOR 2013, Proceedings
T2 - 10th International Conference on the Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, CPAIOR 2013
Y2 - 18 May 2013 through 22 May 2013
ER -