Corpus ID: 52126146

Modelling Langford's Problem: A Viewpoint for Search

@article{Akgun2018ModellingLP,
  title={Modelling Langford's Problem: A Viewpoint for Search},
  author={Ozgur Akgun and Ian Miguel},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.09847}
}
The performance of enumerating all solutions to an instance of Langford's Problem is sensitive to the model and the search strategy. In this paper we compare the performance of a large variety of models, all derived from two base viewpoints. We empirically show that a channelled model with a static branching order on one of the viewpoints offers the best performance out of all the options we consider. Surprisingly, one of the base models proves very effective for propagation, while the other… Expand
Reformulations of Constraint Satisfaction Problems: A Survey
Model reformulation plays an important role in improving models, reducing search space so that solutions can be found faster. Hence we categorise model reformulation into three types: a model isExpand

References

SHOWING 1-10 OF 19 REFERENCES
Boosting Systematic Search by Weighting Constraints
TLDR
A dynamic and adaptive variable ordering heuristic which guides systematic search toward inconsistent or hard parts of a Constraint Satisfaction Problem (CSP) and which avoids some trashing by first instantiating variables involved in the constraints that have frequently participated in dead-end situations. Expand
Minion: A Fast Scalable Constraint Solver
TLDR
Minion is a general-purpose constraint solver, with an expressive input language based on the common constraint modelling device of matrix models, which makes it a substantial step towards Puget's 'Model and Run' constraint solving paradigm. Expand
Automatically Improving Constraint Models in Savile Row through Associative-Commutative Common Subexpression Elimination
TLDR
It is shown that X-CSE, combined with preprocessing and other reformulations, is a powerful technique for automated modelling of problems containing associative and commutative constraints. Expand
Automatically improving constraint models in Savile Row
TLDR
A new algorithm is introduced and described in detail to perform Associative–Commutative Common Subexpression Elimination (AC-CSE) in constraint problems, significantly improving existing CSE techniques for associative and commutative operators such as +. Expand
Extensible Automated Constraint Modelling
TLDR
The CONJURE system makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE, and it is demonstrated that this set of rules is readily extensible to increase the space of possible constraint models CONJURES can produce. Expand
Increasing Constraint Propagation by Redundant Modeling: an Experience Report
TLDR
This paper describes the experience with a simple modeling and programming approach for increasing the amount of constraint propagation in the constraint solving process, and introduces the notions of CSP model and model redundancy, and shows how mutually redundant models can be combined and connected using channeling constraints. Expand
Permutation Problems and Channelling Constraints
TLDR
This paper performs an extensive theoretical and empirical study of different constraint models, hoping that the results will aid constraint programmers to choose a model for a permutation problem and illustrate a general methodology for comparing different constraints models. Expand
Implementing Efficient All Solutions SAT Solvers
TLDR
The implemented solvers of AllSAT solvers were accurately implemented and comprehensive experiments using a large number of instances and various types of solvers including a few publicly available software revealed the solvers’ characteristics. Expand
Breaking Conditional Symmetry in Automated Constraint Modelling with CONJURE
TLDR
This work presents a systematic method by which the automated constraint modelling tool CONJURE can break conditional symmetry as it enters a model during refinement, and results in the automatic and complete removal of model symmetry for the entire problem class represented by the input specification. Expand
Essence: A constraint language for specifying combinatorial problems
Essence is a formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics. EssenceExpand
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