Improved Linearization of Constraint Programming Models View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Gleb Belov , Peter J. Stuckey , Guido Tack , Mark Wallace

ABSTRACT

Constraint Programming (CP) standardizes many specialized “global constraints” allowing high-level modelling of combinatorial optimization and feasibility problems. Current Mixed-Integer Linear Programming (MIP) technology lacks both a modelling language and a solving mechanism based on high-level constraints. MiniZinc is a solver-independent CP modelling language. The solver interface works by translating a MiniZinc model into the simpler language FlatZinc. A specific solver can provide its own redefinition library of MiniZinc constraints. This paper describes improvements to the redefinitions for MIP solvers and to the compiler front-end. We discuss known and new translation methods, in particular we introduce a coordinated decomposition for domain constraints. The redefinition library is tested on the benchmarks of the MiniZinc Challenges 2012–2015. Experiments show that the two solving paradigms have rather diverse sets of strengths and weaknesses. We believe this is an important step for modelling languages. It illustrates that the high-level approach of recognizing and naming combinatorial substructure and using this to define a model, common to CP modellers, is equally applicable to those wishing to use MIP solving technology. It also makes the goal of solver-independent modelling one step closer. At least for prototyping, the new front-end frees the modeller from considering the solving technology, extracting very good performance from MIP solvers for high-level CP-style MiniZinc models. More... »

PAGES

49-65

References to SciGraph publications

  • 2011. Optimal Carpet Cutting in PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING – CP 2011
  • 1976-12. Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems in MATHEMATICAL PROGRAMMING
  • 1989-12. Constructing integer programming models by the predicate calculus in ANNALS OF OPERATIONS RESEARCH
  • 2015-07. A constraint-based local search backend for MiniZinc in CONSTRAINTS
  • 2007. Logic, Language, and Computation, 6th International Tbilisi Symposium on Logic, Language, and Computation,TbiLLC 2005 Batumi, Georgia, September 12-16, 2005. Revised Selected Papers in NONE
  • 2012. Integrated Methods for Optimization in NONE
  • 2007. MiniZinc: Towards a Standard CP Modelling Language in PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING – CP 2007
  • 2010-07. Philosophy of the MiniZinc challenge in CONSTRAINTS
  • 2000. Linear Formulation of Constraint Programming Models and Hybrid Solvers in PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING – CP 2000
  • 2007. Modeling the Regular Constraint with Integer Programming in INTEGRATION OF AI AND OR TECHNIQUES IN CONSTRAINT PROGRAMMING FOR COMBINATORIAL OPTIMIZATION PROBLEMS
  • 2016. Detecting Semantic Groups in MIP Models in INTEGRATION OF AI AND OR TECHNIQUES IN CONSTRAINT PROGRAMMING
  • 2013. MiniZinc with Functions in INTEGRATION OF AI AND OR TECHNIQUES IN CONSTRAINT PROGRAMMING FOR COMBINATORIAL OPTIMIZATION PROBLEMS
  • 2011-07. Explaining the cumulative propagator in CONSTRAINTS
  • 2013. Nonlinear Optimization Applications Using the GAMS Technology in NONE
  • 2007-03. Global Constraint Catalogue: Past, Present and Future in CONSTRAINTS
  • Book

    TITLE

    Principles and Practice of Constraint Programming

    ISBN

    978-3-319-44952-4
    978-3-319-44953-1

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-44953-1_4

    DOI

    http://dx.doi.org/10.1007/978-3-319-44953-1_4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1032966015


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