SAT and Hybrid Models of the Car Sequencing Problem

  • Christian Artigues
  • Emmanuel Hebrard
  • Valentin Mayer-Eichberger
  • Mohamed Siala
  • Toby Walsh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8451)


We compare both pure SAT and hybrid CP/SAT models for solving car sequencing problems, and close 13 out of the 23 large open instances in CSPLib. Three features of these models are crucial to improving the state of the art in this domain. For quickly finding solutions, advanced CP heuristics are important and good propagation (either by a specialized propagator or by a sophisticated SAT encoding that simulates one) is necessary. For proving infeasibility, clause learning in the SAT solver is critical. Our models contain a number of novelties. In our hybrid models, for example, we develop a linear time mechanism for explaining failure and pruning the AtMostSeqCard constraint. In our SAT models, we give powerful encodings for the same constraint. Our research demonstrates the strength and complementarity of SAT and hybrid methods for solving difficult sequencing problems.


Constraint Programming Conjunctive Normal Form Cardinality Constraint Conjunctive Normal Form Formula Constraint Programming Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Christian Artigues
    • 1
    • 2
  • Emmanuel Hebrard
    • 1
    • 2
  • Valentin Mayer-Eichberger
    • 3
    • 4
  • Mohamed Siala
    • 1
    • 5
  • Toby Walsh
    • 3
    • 4
  1. 1.CNRS, LAASToulouseFrance
  2. 2.Univ de Toulouse, LAASToulouseFrance
  3. 3.NICTAAustralia
  4. 4.University of New South WalesAustralia
  5. 5.Univ de Toulouse, INSA, LAASToulouseFrance

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