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SUNNY-CP and the MiniZinc challenge*

  • ROBERTO AMADINI (a1), MAURIZIO GABBRIELLI (a2) and JACOPO MAURO (a3)
Abstract
Abstract

In Constraint Programming, a portfolio solver combines a variety of different constraint solvers for solving a given problem. This fairly recent approach enables to significantly boost the performance of single solvers, especially when multicore architectures are exploited. In this work, we give a brief overview of the portfolio solver sunny-cp, and we discuss its performance in the MiniZinc Challenge—the annual international competition for Constraint Programming solvers—where it won two gold medals in 2015 and 2016.

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This work was supported by the EU project FP7-644298 HyVar: Scalable Hybrid Variability for Distributed, Evolving Software Systems

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Amadini R., Biselli F., Gabbrielli M., Liu T. and Mauro J. 2015. SUNNY for algorithm selection: A preliminary study. In Proc. 30th Italian Conference on Computational Logic, Ancona D., Maratea M. and Mascardi V., Eds. CEUR Workshop Proceedings, vol. 1459, July 1–3, 2015, Genova, Italy, CEUR-WS.org, 202–206.
Amadini R., Gabbrielli M. and Mauro J. 2014a. An enhanced features extractor for a portfolio of constraint solvers. In Symposium on Applied Computing, SAC 2014, Cho Y., Shin S. Y., Kim S., Hung C., and Hong J., Eds. March 24–28, 2014, ACM, Gyeongju, Republic of Korea, 13571359.
Amadini R., Gabbrielli M. and Mauro J. 2014b. SUNNY: A lazy portfolio approach for constraint solving. In TPLP 14, 509524.
Amadini R., Gabbrielli M. and Mauro J. 2015a. A Multicore tool for constraint solving. In Proc. of the 24th International Joint Conference on Artificial Intelligence, IJCAI 2015, Yang Q. and Wooldridge M., Eds. July 25–31, 2015, AAAI Press, Buenos Aires, Argentina, 232238.
Amadini R., Gabbrielli M. and Mauro J. 2015b. SUNNY-CP: A sequential CP portfolio solver. In Proc. of the 30th Annual ACM Symposium on Applied Computing, Wainwright R. L., Corchado J. M., Bechini A. and Hong J., Eds. April 13–17, 2015, ACM, Salamanca, Spain, 18611867.
Amadini R., Gabbrielli M. and Mauro J. 2015c. Why CP portfolio solvers are (under)utilized? Issues and challenges. In Proc. of Logic-Based Program Synthesis and Transformation – 25th International Symposium, LOPSTR 2015, Falaschi M., Ed. Revised Selected Papers, Lecture Notes in Computer Science, July 13–15, 2015, vol. 9527. Springer, Siena, Italy, 349364.
Amadini R., Gabbrielli M. and Mauro J. 2016a. Parallelizing constraint solvers for hard RCPSP instances. In Learning and Intelligent Optimization – 10th International Conference, LION 10, Festa P., Sellmann M. and Vanschoren J., Eds. Revised Selected Papers, Lecture Notes in Computer Science, May 29–June 1, 2016, vol. 10079. Springer, Ischia, Italy, 227233.
Amadini R., Gabbrielli M. and Mauro J. 2016b. Portfolio approaches for constraint optimization problems. Annals of Mathematics and Artificial Intelligence 76, 12, 229246.
Amadini R. and Stuckey P. J. 2014. Sequential time splitting and bounds communication for a portfolio of optimization solvers. In Proc. of Principles and Practice of Constraint Programming – 20th International Conference, CP 2014, O'Sullivan B., Ed. Lecture Notes in Computer Science, September 8–12, 2014, vol. 8656. Springer, Lyon, France, 108124.
Belov G., Stuckey P. J., Tack G. and Wallace M. 2016. Improved linearization of constraint programming models. In Proc. of Principles and Practice of Constraint Programming – 22nd International Conference, CP 2016, Rueher M., Ed. Lecture Notes in Computer Science, September 5–9, 2016, vol. 9892. Springer, Toulouse, France, 4965.
Chevaleyre Y., Endriss U., Lang J. and Maudet N. 2007. A short introduction to computational social choice. In Proc. of SOFSEM 2007: Theory and Practice of Computer Science, 33rd Conference on Current Trends in Theory and Practice of Computer Science, van Leeuwen J., Italiano G. F., van der Hoek W., Meinel C., Sack H. and Plasil F., Eds. Lecture Notes in Computer Science, January 20–26, 2007, vol. 4362. Springer, Harrachov, Czech Republic, 5169.
Chuffed. 2016. Chuffed Solver. URL: https://github.com/geoffchu/chuffed.
coseal. 2014. Algorithm Selection Library. URL: http://www.coseal.net/.
de Cat B., Bogaerts B., Devriendt J. and Denecker M. 2013. Model expansion in the presence of function symbols using constraint programming. In Proc. of IEEE 25th International Conference on Tools with Artificial Intelligence, November 4–6, 2013, IEEE Computer Society, Herndon, VA, USA, 10681075.
Gomes C. P. and Selman B. 2001. Algorithm portfolios. Artificial Intelligence 126, 1–2, 4362.
Hebrard E., O'Mahony E. and O'Sullivan B. 2010. Constraint programming and combinatorial optimisation in numberjack. In Proc. of Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 7th International Conference, CPAIOR 2010, Lodi A., Milano M. and Toth P., Eds. Lecture Notes in Computer Science, June 14–18, 2010, vol. 6140. Springer, Bologna, Italy, 181185.
Hutter F., Xu L., Hoos H. H. and Leyton-Brown K. 2014. Algorithm runtime prediction: Methods & evaluation. Artificial Intelligence 206, 79111.
iZplus. 2016. iZplus Solver Description. URL: https://www.minizinc.org/challenge2016/description_izplus.txt.
JaCoP. 2016. JaCoP Solver. URL: http://jacop.osolpro.com/.
Kotthoff L. 2014. Algorithm selection for combinatorial search problems: A survey. AI Magazine 35, 3, 4860.
Kotthoff L. 2015. ICON challenge on algorithm selection. CoRR abs/1511.04326.
Lindauer M., Bergdoll R. and Hutter F. 2016. An empirical study of per-instance algorithm scheduling. In Proc. of Learning and Intelligent Optimization – 10th International Conference, LION 10, Festa P., Sellmann M. and Vanschoren J., Eds. Revised Selected Papers, Lecture Notes in Computer Science, May 29–June 1, 2016, vol. 10079. Springer, Ischia, Italy, 253259.
Malitsky Y., Sabharwal A., Samulowitz H. and Sellmann M. 2012. Parallel SAT Solver Selection and Scheduling. In Proc. of Principles and Practice of Constraint Programming – 18th International Conference, CP 2012, Milano M., Ed. Lecture Notes in Computer Science, October 8–12, 2012, vol. 7514. Springer, Québec City, Canada, 512526.
MiniZinc. 2016. MiniZinc Software. URL: https://www.minizinc.org/software.html.
Mistral. 2016. Mistral Solver. URL: https://github.com/ehebrard/Mistral-2.0.
Nethercote N., Stuckey P. J., Becket R., Brand S., Duck G. J. and Tack G. 2007. MiniZinc: Towards a standard CP modelling language. In Proc. of Principles and Practice of Constraint Programming – CP 2007, 13th International Conference, CP 2007, Bessiere C., Ed. Lecture Notes in Computer Science, September 23–27, 2007, vol. 4741. Springer, Providence, RI, USA, 529543.
O'Mahony E., Hebrard E., Holland A., Nugent C. and O'Sullivan B. 2008, August. Using case-based reasoning in an algorithm portfolio for constraint solving. In Irish conference on artificial intelligence and cognitive science (pp. 210-216).
Opturion CPX. 2016. Opturion CPX Solver. URL: http://www.opturion.com/.
OR-Tools. 2016. OR-Tools Solver. URL: https://github.com/google/or-tools.
Prud'homme C., Fages J.-G. and Lorca X. 2016. Choco Documentation. TASC, INRIA Rennes, LINA CNRS UMR 6241, COSLING S.A.S.
Rice J. R. 1976. The Algorithm Selection Problem. Advances in Computers 15, 65118.
Rossi F., Beek P. V. and Walsh T. 2006. Handbook of Constraint Programming (Foundations of Artificial Intelligence). Elsevier Science Inc., New York, NY, USA.
Sabharwal A. and Samulowitz H. 2014. Insights into Parallelism with Intensive Knowledge Sharing. In Proc. of Principles and Practice of Constraint Programming – 20th International Conference, CP 2014, O'Sullivan B., Ed. Lecture Notes in Computer Science, September 8–12, 2014, vol. 8656. Springer, Lyon, France, 655671.
Smith-Miles K. 2008. Cross-disciplinary perspectives on meta-learning for algorithm selection. ACM Computing Surveys 41, 1, 6:16:25.
Stuckey P. J., Feydy T., Schutt A., Tack G. and Fischer J. 2014. The MiniZinc challenge 2008–2013. AI Magazine 35, 2, 5560.
Veksler M. and Strichman O. 2016. Learning general constraints in CSP. Artificial Intelligence 238, 135153.
Zhou N. and Kjellerstrand H. 2016. The Picat-SAT Compiler. In Practical Aspects of Declarative Languages – 18th International Symposium, PADL 2016, Gavanelli M. and Reppy J. H., Eds. Lecture Notes in Computer Science, January 18–19, 2016, vol. 9585. Springer, St. Petersburg, FL, USA, 4862.
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Theory and Practice of Logic Programming
  • ISSN: 1471-0684
  • EISSN: 1475-3081
  • URL: /core/journals/theory-and-practice-of-logic-programming
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