TY - JOUR
KW - Programming
KW - Algorithms
KW - Constraint
AU - Roberto Amadini
AU - Jacopo Mauro
AU - Maurizio Gabbrielli
AB - 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.
IS - Regular Issue
M1 - 7
N2 - 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.
PY - 2016
SP - 81
EP - 86
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - An Extensive Evaluation of Portfolio Approaches for Constraint Satisfaction Problems
UR - http://www.ijimai.org/journal/sites/default/files/files/2016/05/ijimai20163_7_12_pdf_13932.pdf
VL - 3
SN - 1989-1660
ER -