Invited Session Tue.2.H 1058

Tuesday, 13:15 - 14:45 h, Room: H 1058

Cluster 10: Implementations & software [...]

Software for constraint programming

 

Chair: Paul Shaw

 

 

Tuesday, 13:15 - 13:40 h, Room: H 1058, Talk 1

Paul Shaw
Automatic search in CP optimizer

 

Abstract:
Automatic (or autonomous) search is a subject which has gained interest in the CP community over the last few years, in response to a need to simplify the use of constraint programming. IBM (previously ILOG) has been at the forefront of this effort with the implementation of the CP Optimizer component of CPLEX Optimization Studio. CP Optimizer includes in its automatic search procedure diverse elements such as local search, learning techniques, and linear programming. In this talk, we briefly present CP Optimizer and the key elements of its automatic search.

 

 

Tuesday, 13:45 - 14:10 h, Room: H 1058, Talk 2

Peter Nightingale
Watched literals and generating propagators in constraint programming

Coauthors: Ian P. Gent, Christopher Jefferson, Ian Miguel

 

Abstract:
Many modern constraint solvers interleave constraint reasoning (propagation) with a complete search. In systems like these, the efficiency of propagation is vital, because the solver spends almost all of its time doing propagation. In this talk I will present a number of techniques developed at St Andrews to improve the efficiency of propagation, in some cases by orders of magnitude.
Watched literals are used in SAT (propositional satisfiability) solvers where they are helpful in dealing with the huge number of long constraints generated by conflict learning. I will discuss porting watched literals to CP, and when this is useful. I will also talk about automatic generation of propagation algorithms, and when this can outperform even hand-optimised algorithms.
Most of the techniques are implemented in the Minion solver. I will give an overview of Minion's features, strengths and weaknesses.

 

 

Tuesday, 14:15 - 14:40 h, Room: H 1058, Talk 3

Guido Tack
Towards MiniZinc 2.0

Coauthors: Sebastian Brand, Mark Brown, Thibaut Feydy, Julien Fischer, Maria Garcia de la Banda, Peter J. Stuckey, Mark Wallace

 

Abstract:
MiniZinc is a language for modelling combinatorial problems. It aims at striking the right balance between expressiveness on the one hand, and support for different solvers on the other. To this end, MiniZinc provides a library of predicates defining global constraints, and a generic translation to FlatZinc, a low-level language that is easy to support by different solvers.
Since its inception in 2006, MiniZinc has gained considerable momentum. In its current version 1.5, the G12 MiniZinc distribution provides a complete, stable, usable toolchain for modelling and solving combinatorial problems. Its library contains definitions of over 150 global constraints, and there are backends for a variety of different solvers, from constraint programming, to mathematical programming, to SAT and SMT.
The next major milestone will conservatively extend the language with features from full Zinc, add more control over the search, and open up the toolchain to allow for customisation of the translation and easier integration into existing software.
This presentation gives an overview of the MiniZinc system, what is planned for version 2.0, and the techniques required to implement it.

 

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