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A Stochastic Continuous Optimization Backend for MiniZinc with Applications to Geometrical Placement Problems

  • Conference paper
  • First Online:
Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9676))

Abstract

MiniZinc is a solver-independent constraint modeling language which is increasingly used in the constraint programming community. It can be used to compare different solvers which are currently based on either Constraint Programming, Boolean satisfiability, Mixed Integer Linear Programming, and recently Local Search. In this paper we present a stochastic continuous optimization backend for MiniZinc models over real numbers. More specifically, we describe the translation of FlatZinc models into objective functions over the reals, and their use as fitness functions for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) solver. We illustrate this approach with the declarative modeling and solving of hard geometrical placement problems, motivated by packing applications in logistics involving mixed square-curved shapes and complex shapes defined by Bézier curves.

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Notes

  1. 1.

    https://code.google.com/p/or-tools/.

  2. 2.

    https://github.com/chocoteam/choco-parsers.

  3. 3.

    http://eclipseclp.org/doc/bips/lib_public/flatzinc/.

  4. 4.

    http://www.gecode.org/flatzinc.html.

  5. 5.

    http://www.opturion.com/cpx.

  6. 6.

    http://www.minizinc.org/challenge2014/descriptionizplus.txt.

  7. 7.

    http://www.ibex-lib.org.

  8. 8.

    https://www.lri.fr/~hansen/cmaesintro.html.

References

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Acknowledgements

This work has been funded by the ANR Blanc Simi2 Net-WMS-2 grant ANR-11-BS02-0005. We would like to thank all the partners of this project for fruitful discussions.

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Authors and Affiliations

  1. Inria Paris-Rocquencourt, Team Lifeware, Rocquencourt, France

    Thierry Martinez & François Fages

  2. KLS-Optim, Les Ulis, France

    Abder Aggoun

Authors
  1. Thierry Martinez
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  2. François Fages
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  3. Abder Aggoun
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Corresponding author

Correspondence to Thierry Martinez .

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Editors and Affiliations

  1. Université Laval, Quebec, Québec, Canada

    Claude-Guy Quimper

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© 2016 Springer International Publishing Switzerland

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Martinez, T., Fages, F., Aggoun, A. (2016). A Stochastic Continuous Optimization Backend for MiniZinc with Applications to Geometrical Placement Problems. In: Quimper, CG. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2016. Lecture Notes in Computer Science(), vol 9676. Springer, Cham. https://doi.org/10.1007/978-3-319-33954-2_19

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  • DOI: https://doi.org/10.1007/978-3-319-33954-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33953-5

  • Online ISBN: 978-3-319-33954-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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