Publications

Citing MiniZinc

If you use MiniZinc in your own research or would like to acknowlegde it in a publication, please use the following references.

  • N. Nethercote, P.J. Stuckey, R. Becket, S. Brand, G.J. Duck, and G. Tack. MiniZinc: Towards a standard CP modelling language. In C. Bessiere, editor, Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming, volume 4741 of LNCS, pages 529–543. Springer, 2007. more...
    There is no standard modelling language for constraint programming (CP) problems. Most solvers have their own modelling language. This makes it difficult for modellers to experiment with different solvers for a problem. In this paper we present MiniZinc, a simple but expressive CP modelling language which is suitable for modelling problems for a range of solvers and provides a reasonable compromise between many design possibilities. Equally importantly, we also propose a low-level solver-input language called FlatZinc, and a straightforward translation from MiniZinc to FlatZinc that preserves all solver-supported global constraints. This lets a solver writer support MiniZinc with a minimum of effort - they only need to provide a simple FlatZinc front-end to their solver, and then combine it with an existing MiniZinc-to-FlatZinc translator. Such a front-end may then serve as a stepping stone towards a full MiniZinc implementation that is more tailored to the particular solver. A standard language for modelling CP problems will encourage experimentation with and comparisons between different solvers. Although MiniZinc is not perfect - no standard modelling language will be - we believe its simplicity, expressiveness, and ease of implementation make it a practical choice for a standard language.

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  • Peter J. Stuckey, Thibaut Feydy, Andreas Schutt, Guido Tack, and Julien Fischer. The MiniZinc challenge 2008-2013. AI Magazine, 35(2):55–60, 2014, 2014. more...
    MiniZinc is a solver agnostic modeling language for defining and solver combinatorial satisfaction and optimization problems. MiniZinc provides a solver independent modeling language which is now supported by constraint programming solvers, mixed integer programming solvers, SAT and SAT modulo theory solvers, and hybrid solvers. Since 2008 we have run the MiniZinc challenge every year, which compares and contrasts the different strengths of different solvers and solving technologies on a set of MiniZinc models. Here we report on what we have learnt from running the competition for 6 years.

    • Papers defining the MiniZinc or Zinc languages and extensions

  • P.J. Stuckey and G. Tack. Compiling Conditional Constraints. In Simon de Givry and Thomas Schiex, editors, Proceedings of the 25th International Conference on Principles and Practice of Constraint Programming. Springer. To appear., 2019. more...
    Conditionals are a core concept in all programming languages. They are also a natural and powerful mechanism for expressing complex constraints in constraint modelling languages. The behaviour of conditionals is complicated by undefinedness. In this paper we show how to most effectively translate conditional constraints for underlying solvers. We show that the simple translation into implications can be improved, at least in terms of reasoning strength, for both constraint programming and mixed integer programming solvers. Unit testing shows that the new translations are more efficient, but the benefits are not so clear on full models where the interaction with other features such as learning is more complicated.

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  • Gleb Belov, Peter J. Stuckey, Guido Tack, Mark Wallace. Improved Linearization of Constraint Programming Models. In M. Rueher, editor, Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings. LNCS 9892, pp. 49-65, Springer, 2016.
  • Andrea Rendl, Tias Guns, Peter J. Stuckey, and Guido Tack. MiniSearch: a solver-independent meta-search language for MiniZinc. In Gilles Pesant, editor, CP, p. 376-392. Springer, 2015.
  • Kevin Leo and Guido Tack. Multi-pass high-level presolving. In Qiang Yang and Michael Wooldridge, editors, IJCAI, pp. 346–352. AAAI Press, 2015.
  • Andrea Rendl, Guido Tack, and Peter J. Stuckey. Stochastic MiniZinc. In B. O’Sullivan, editor, Proceedings of the 20th International Conference on Principles and Practice of Constraint Programming, volume 8656 of LNCS, pages 636–645. Springer, 2014.
  • Christopher Mears, Andreas Schutt, Peter J. Stuckey, Guido Tack, Kim Marriott, and Mark Wallace. Modelling with option types in MiniZinc. In Proceedings of the 11th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming, number 8451 in LNCS, pages 88–103. Springer, 2014.
  • Geoffrey Chu and Peter J. Stuckey. Nested constraint programs. In B. O’Sullivan, editor, Proceedings of the 20th International Conference on Principles and Practice of Constraint Programming, volume 8656 of LNCS, pages 240–255. Springer, 2014.
  • Peter J. Stuckey and Guido Tack. MiniZinc with functions. In Proceedings of the 10th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming, number 7874 in LNCS, pages 268–283. Springer, 2013.
  • T. Schrijvers, G. Tack, P. Wuille, H. Samulowitz, and P.J. Stuckey. Search combinators. Constraints, 18(2):269–305, 2013.
  • T. Schrijvers, G. Tack, P. Wuille, H. Samulowitz, and P.J. Stuckey. Search combinators. In J.H.M. Lee, editor, Proceedings of the 17th International Conference on Principles and Practice of Constraint Programming, volume 6876 of LNCS, pages 774–788. Springer, 2011.
  • J. Puchinger, P.J. Stuckey, M. Wallace, and S. Brand. Dantzig-wolfe decomposition and branch-and-price solving in G12. Constraints, 16(1):77–99, 2011.
  • T. Feydy, Z. Somogyi, and P.J. Stuckey. Half-reification and flattening. In J.H.M. Lee, editor, Proceedings of the 17th International Conference on Principles and Practice of Constraint Programming, volume 6876 of LNCS, pages 286–301. Springer, 2011.
  • Alan Frisch and Peter J. Stuckey. The proper treatment of undefinedness in constraint languages. In I. Gent, editor, Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming, volume 5732 of LNCS, pages 367–382. Springer-Verlag, 2009.
  • Kim Marriott, Nicholas Nethercote, R. Rafeh, Peter J. Stuckey, Maria Garcia de la Banda, and Mark Wallace. The design of the Zinc modelling language. Constraints, 13(3):229–267, 2008.
  • Sebastian Brand, Gregory J. Duck, Jakob Puchinger, and Peter J. Stuckey. Flexible, rule-based constraint model linearisation. In P. Hudak and D.S. Warren, editors, Proceedings of Tenth International Symposium on Practical Aspects of Declarative Languages, number 4902 in LNCS, pages 68–83. Springer-Verlag, 2008.

    • Papers using MiniZinc or Zinc

  • Ria Szeredi and Andreas Schutt. Modelling and Solving Multi-Mode Resource-Constrained Project Scheduling. In M. Rueher, editor, Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings. LNCS 9892, pp. 483-492, Springer, 2016.
  • Maxim Shishmarev, Christopher Mears, Guido Tack, Maria Garcia de la Banda. Learning from Learning Solvers. In M. Rueher, editor, Principles and Practice of Constraint Programming - 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings. LNCS 9892, pp. 455-472, Springer, 2016.
  • Maxim Shishmarev, Christopher Mears, Guido Tack, and Maria Garcia de la Banda. Visual search tree profiling. In Constraints 21(1), pp. 77–94, 2016.
  • Tias Guns, Anton Dries, Siegfried Nijssen, Guido Tack, and Luc De Raedt. MiningZinc: A declarative framework for constraint-based mining. In Artificial Intelligence, 2015.
  • Geoffrey Chu and Peter J. Stuckey. Learning value heuristics for constraint programming. In Proceedings of Twelfth International Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CPAIOR 2015), volume 9075 of LNCS, pages 108–123, Springer, 2015.
  • Christina Burt, Nir Lipovetzky, Adrian Pearce, and Peter J. Stuckey. Scheduling with fixed maintenance, shared resources and nonlinear feedrate constraints: a mine planning case study. In Proceedings of Twelfth International Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CPAIOR 2015), volume 9075 of LNCS, pages 91–107, Springer, 2015.
  • Gustav Björdal, Jean-Noël Monette, Pierre Flener, Justin Pearson. A constraint-based local search backend for MiniZinc. Constraints 20(3):325-345, 2015.
  • Kathryn Francis and Peter J. Stuckey. Loop untangling. In B. O’Sullivan, editor, Proceedings of the 20th International Conference on Principles and Practice of Constraint Programming, volume 8656 of LNCS, pages 340–355, Springer, 2014.
  • Kathryn Francis and Peter J. Stuckey.. Explaining circuit propagation. Constraints, 19(1):1–29, 2014.
  • Broderick Crawford, Ricardo Soto, Carolina Zec, Eric Monfroy, Fernando Paredes. Easy Modeling of Open Pit Mining Problems via Constraint Programming. HCI International 2014 - Posters’ Extended Abstracts, Communications in Computer and Information Science Volume 434, pp 519-522, 2014.
  • Gleb Belov, Natashia Boland, Martin W.P. Savelsbergh, and Peter J. Stuckey. Local search for a cargo assembly planning problem. In Proceedings of the 11th Interna- tional Conference on Integration of Artificial Intelligence (AI) and Operations Re- search (OR) techniques in Constraint Programming, number 8451 in LNCS, pages 159–175, Springer, 2014.
  • Roberto Amadini, Maurizio Gabbrielli, and Jacopo Mauro. An enhanced features extractor for a portfolio of constraint solvers. In Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC '14). ACM, New York, NY, USA, 1357-1359, 2014.
  • Roberto Amadini and Peter J. Stuckey. Sequential time splitting and bounds communication for a portfolio of optimization solvers. In B. O’Sullivan, editor, Proceedings of the 20th International Conference on Principles and Practice of Constraint Programming, volume 8656 of LNCS, pages 108–124, Springer, 2014.
  • Andreas Schutt, Thibaut Feydy, and Peter J. Stuckey. Explaining time-table-edge-finding propagation for the cumulative resource constraint. In Proceedings of the 10th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming, number 7874 in LNCS, pages 234–250, Springer, 2013.
  • Andreas Schutt, Thibaut Feydy, and Peter J. Stuckey. Scheduling optional tasks with explanation. In C. Schulte, editor, Proceedings of the 19th International Conference on Principles and Practice of Constraint Programming, volume 8124 of LNCS, pages 628–644, Springer, 2013.
  • Andreas Schutt, Thibaut Feydy, Peter J. Stuckey, and Mark Wallace.. Solving RCPSP/max by lazy clause generation. Journal of Scheduling, 16(3):273–289, 2013.
  • Kevin Leo, Christopher Mears, Guido Tack, Maria Garcia de la Banda. Globalizing Constraint Models. Principles and Practice of Constraint Programming - 19th International Conference, CP 2013, Uppsala, Sweden, September 16-20, 2013, Proceedings, pp. 432-447, Springer, 2013.
  • Hewson, JA, Anderson, P and Gordon, AD. Constraint-based Autonomic Reconfiguration. , 2013.
  • Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen and Luc De Raedt. MiningZinc: A Modeling Language for Constraint-based Mining. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, pp. 1365-1372, 2013.
  • Kathryn Francis, Jorge Navas, and Peter J. Stuckey. Modelling destructive assignments. In C. Schulte, editor, Proceedings of the 19th International Conference on Principles and Practice of Constraint Programming, volume 8124 of LNCS, pages 315–330, Springer, 2013.
  • Geoffrey Chu and Peter J. Stuckey. Dominance driven search. In C. Schulte, editor, Proceedings of the 19th International Conference on Principles and Practice of Constraint Programming, volume 8124 of LNCS, pages 217–229, Springer, 2013.
  • Rafael Caballero, Peter J. Stuckey, and Antonio Tenorio-Fornes. Finite type extensions in constraint programming. In T. Schrijvers, editor, Proceedings of the 15th International Symposium on Principles and Practice of Declarative Programming, pages 217–228, ACM Press, 2013.
  • Claudio León de la Barra, Ricardo Soto, Broderick Crawford, Camila Allendes, Hans Berendsen, Eric Monfroy. Modeling the Portfolio Selection Problem with Constraint Programming. HCI International 2013 - Posters’ Extended Abstracts, Communications in Computer and Information Science Volume 373, pp 645-649, 2013.
  • Rehan Abdul Aziz, Peter J. Stuckey, and Zoltan Somogyi. Inductive definitions in constraint programming. In Proceedings of the Thirty-Sixth Australasian Computer Science Conference (ACSC 2013), pages 41–50, 2013.
  • Rehan Abdul Aziz, Geoffrey Chu, and Peter J. Stuckey.. Stable model semantics for founded bounds.. Theory and Practice of Logic Programming, 13(4–5):517–532, 2013. Proceedings of the 29th International Conference on Logic Programming, 2013.
  • Mark Przepiora, Reza Karimpour, and Guenther Ruhe. A hybrid release planning method and its empirical justification. In Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement (ESEM '12). ACM, New York, NY, USA, pp. 115-118, 2012.
  • Jinbo Huang. Search Strategy Simulation in Constraint Booleanization. Principles of Knowledge Representation and Reasoning: Proceedings of the Thirteenth International Conference, KR 2012, Rome, Italy, June 10-14, 2012, AAAI Press, 2012.
  • John A. Hewson, Paul Anderson, and Andrew D. Gordon. A declarative approach to automated configuration. In Proceedings of the 26th international conference on Large Installation System Administration: strategies, tools, and techniques (lisa'12), USENIX Association, Berkeley, CA, USA, 51-66, 2012.
  • Kathryn Francis, Sebastian Brand, and Peter J. Stuckey. Optimization modelling for software developers. In M. Milano, editor, Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming, number 7514 in LNCS, pages 274–289, Springer, 2012.
  • N. Downing, T. Feydy, and P.J. Stuckey. Explaining alldifferent. In M. Reynolds and B. Thomas, editors, Proceedings of the Australasian Computer Science Conference (ACSC 2012), volume 122 of CRPIT, pages 115–124, Melbourne, Australia, ACS, 2012.
  • N. Downing, T. Feydy, and P.J. Stuckey. Explaining flow-based propagation. In N. Beldiceanu, N. Jussien, and E. Pinson, editors, International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR), number 7298 in LNCS, pages 146–162, Springer, 2012.
  • G. Chu and P.J. Stuckey. A generic method for systematically identifying and exploiting dominance relations. In M. Milano, editor, Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming, number 7514 in LNCS, pages 6–22, Springer, 2012.
  • G. Chu and P.J. Stuckey. Inter-problem nogood learning in constraint programming. In M. Milano, editor, Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming, number 7514 in LNCS, pages 238–247, Springer, 2012.
  • G. Chu, M. Garcia de la Banda, and P.J. Stuckey. Exploiting subproblem dominance in constraint programming. Constraints, 17(1):1–38, 2012.
  • G. Chu and P.J. Stuckey. A complete solution to the maximum density still life problem. Artificial Intelligence, 184–185:1–16, 2012.
  • A. Schutt, T. Feydy, P.J. Stuckey, and M. Wallace. Explaining the cumulative propagator. Constraints, 16(3):250–282, 2011.
  • Mehani, O. ; Boreli, R. ; Maher, M. ; Ernst, T.. User- and application-centric multihomed flow management. IEEE 36th Conference on Local Computer Networks (LCN), 2011.
  • Christopher Mears, Todd Niven, Marcel Jackson, Mark Wallace. Proving Symmetries by Model Transformation. Principles and Practice of Constraint Programming – CP 2011, Lecture Notes in Computer Science Volume 6876, pp 591-605, Springer, 2011.
  • P.J. Stuckey, R. Becket, and J. Fischer. Philosophy of the MiniZinc challenge. Constraints, 15(3):307–316, 2010.
  • Tripti Saxena and Gabor Karsai. The GDSE framework: a meta-tool for automated design space exploration. In Proceedings of the 10th Workshop on Domain-Specific Modeling (DSM '10), ACM, New York, NY, USA, Article 15, 6 pages, 2010.
  • Qinghua Lu. MiniMASC+MiniZinc: An Autonomic Business-Driven Decision Making Middleware for Adaptation of Web Service Compositions. Ubiquitous Intelligence & Computing and 7th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2010.
  • G. Chu, M. Garcia de la Banda, and P.J. Stuckey. Automatically exploiting subproblem equivalence in constraint programming. In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, volume 6140 of LNCS, pages 71–86, Springer, 2010.
  • Miquel Bofill, Josep Suy, Mateu Villaret. A System for Solving Constraint Satisfaction Problems with SMT. Theory and Applications of Satisfiability Testing – SAT 2010, Lecture Notes in Computer Science Volume 6175, pp 300-305, Springer, 2010.
  • A. Schutt, T. Feydy, P.J. Stuckey, and M. Wallace. Why cumultive decomposition is not as bad as it sounds. In I. Gent, editor, Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming, volume 5732 of LNCS, pages 746–761, Springer-Verlag, 2009.
  • T. Feydy and P.J. Stuckey. Lazy clause generation reengineered. In I. Gent, editor, Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming, volume 5732 of LNCS, pages 352–366, Springer-Verlag, 2009.
  • Jinbo Huang. Universal Booleanization of Constraint Models. Principles and Practice of Constraint Programming, Lecture Notes in Computer Science Volume 5202, pp 144-158, Springer, 2008.

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