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111
Adaptive Constraint Satisfaction
 WORKSHOP OF THE UK PLANNING AND SCHEDULING
, 1996
"... Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm fo ..."
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Cited by 950 (43 self)
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Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm for solving all problems. At the same time, a consensus appears to have developed to the effect that it is unlikely that any single algorithm is always the best choice for all classes of problem. In this paper we argue that an adaptive approach should play an important part in constraint satisfaction. This approach relaxes the commitment to using a single algorithm once search commences. As a result, we claim that it is possible to undertake a more focused approach to problem solving, allowing for the correction of bad algorithm choices and for capitalising on opportunities for gain by dynamically changing to more suitable candidates.
Constraint Programming
, 1995
"... Constraint programming is a paradigm that is tailored to hard search problems. To date the main application areas are those of planning, scheduling, timetabling, routing, placement, investment, configuration, design and insurance. ..."
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Cited by 318 (9 self)
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Constraint programming is a paradigm that is tailored to hard search problems. To date the main application areas are those of planning, scheduling, timetabling, routing, placement, investment, configuration, design and insurance.
Model Checking in CLP
, 1999
"... We show that Constraint Logic Programming (CLP) can serve as a conceptual basis and as a practical implementation platform for the model checking of infinitestate systems. Our contributions are: (1) a semanticspreserving translation of concurrent systems into CLP programs, (2) a method for verifyi ..."
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Cited by 101 (28 self)
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We show that Constraint Logic Programming (CLP) can serve as a conceptual basis and as a practical implementation platform for the model checking of infinitestate systems. Our contributions are: (1) a semanticspreserving translation of concurrent systems into CLP programs, (2) a method for verifying safety and liveness properties on the CLP programs produced by the translation. We have implemented the method in a CLP system and verified wellknown examples of infinitestate programs over integers, using here linear constraints as opposed to Presburger arithmetic as in previous solutions.
Semiringbased Constraint Logic Programming: Syntax and Semantics
, 2001
"... this paper, more simply, soft constraint problems. ..."
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Cited by 56 (28 self)
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this paper, more simply, soft constraint problems.
Scheduling a Major College Basketball Conference  Revisited
 Operations Research
, 2002
"... Nemhauser and Trick presented the problem of nding a timetable for the 1997/98 Atlantic Coast Conference (ACC) in basketball. Their solution, found with a combination of integer programming and exhaustive enumeration, was accepted by the ACC. ..."
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Cited by 39 (6 self)
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Nemhauser and Trick presented the problem of nding a timetable for the 1997/98 Atlantic Coast Conference (ACC) in basketball. Their solution, found with a combination of integer programming and exhaustive enumeration, was accepted by the ACC.
A Unifying Framework for Integer and Finite Domain Constraint Programming
, 1997
"... We present a unifying framework for integer linear programming and finite domain constraint programming, which is based on a distinction of primitive and nonprimitive constraints and a general notion of branchandinfer. We compare the two approaches with respect to their modeling and solving capab ..."
Abstract

Cited by 35 (2 self)
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We present a unifying framework for integer linear programming and finite domain constraint programming, which is based on a distinction of primitive and nonprimitive constraints and a general notion of branchandinfer. We compare the two approaches with respect to their modeling and solving capabilities. We introduce symbolic constraint abstractions into integer programming. Finally, we discuss possible combinations of the two approaches.
Data structures for generalised arc consistency for extensional constraints
 In Proceedings of the Twenty Second Conference on Artificial Intelligence
, 2007
"... Extensional (table) constraints are an important tool for attacking combinatorial problems with constraint programming. Recently there has been renewed interest in fast propagation algorithms for these constraints. We describe the use of two alternative data structures for maintaining generalised ar ..."
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Cited by 32 (9 self)
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Extensional (table) constraints are an important tool for attacking combinatorial problems with constraint programming. Recently there has been renewed interest in fast propagation algorithms for these constraints. We describe the use of two alternative data structures for maintaining generalised arc consistency on extensional constraints. The first, the NextDifference list, is novel and has been developed with this application in mind. The second, the trie, is well known but its use in this context is novel. Empirical analyses demonstrate the efficiency of the resulting approaches, both in GACschema, and in the watchedliteral table constraint in Minion.
University course timetabling using constraint handling rules
 Journal of Applied Artificial Intelligence
"... Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied, soft constraints, however, may be violated, but should be satisfied as much as possible. This p ..."
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Cited by 24 (2 self)
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Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied, soft constraints, however, may be violated, but should be satisfied as much as possible. This paper shows how to model our timetabling problem as a partial constraint satisfaction problem and gives a concise finite domain solver implemented with Constraint Handling Rules that, by performing soft constraint propagation, allows for making soft constraints an active part of the problem solving process. Furthermore, we improve efficiency by reusing parts of the timetable of the previous year. Our prototype needs only a few minutes to create a timetable while manual timetabling usually takes a few days. It was presented at the Systems’98 computer fair in Munich and several universities have enquired for it. 1
Propagation algorithms for lexicographic ordering constraints
 Artificial Intelligence
, 2006
"... Finitedomain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finitedomain constraint programming to a problem, it is modelled by a set of constraints on a set of decision variables. A common modelling pat ..."
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Cited by 24 (8 self)
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Finitedomain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finitedomain constraint programming to a problem, it is modelled by a set of constraints on a set of decision variables. A common modelling pattern is the use of matrices of decision variables. The rows and/or columns of these matrices are often symmetric, leading to redundancy in a systematic search for solutions. An effective method of breaking this symmetry is to constrain the assignments of the affected rows and columns to be ordered lexicographically. This paper develops an incremental propagation algorithm, GACLexLeq, that establishes generalised arc consistency on this constraint in O(n) operations, where n is the length of the vectors. Furthermore, this paper shows that decomposing GACLexLeq into primitive constraints available in current finitedomain constraint toolkits reduces the strength or increases the cost of constraint propagation. Also presented are extensions and modifications to the algorithm to handle strict lexicographic ordering, detection of entailment, and vectors of unequal length. Experimental results on a number of domains demonstrate the value of GACLexLeq. 1
A SATbased version space algorithm for acquiring constraint satisfaction problems
 In Proceedings of ECML’05
, 2005
"... Abstract. Constraint programming is rapidly becoming the technology of choice for modelling and solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problem appropriately. The lack of availability of such expertise is a signific ..."
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Cited by 22 (8 self)
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Abstract. Constraint programming is rapidly becoming the technology of choice for modelling and solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problem appropriately. The lack of availability of such expertise is a significant bottleneck to the broader uptake of constraint technology in the real world. We present a new SATbased version space algorithm for acquiring constraint satisfaction problems from examples of solutions and nonsolutions of the target problem. We show how domainspecific knowledge related to constraint redundancy can be exploited in a number of ways using the new algorithm. We highlight a number of advantages of our approach. Finally, we empirically demonstrate the algorithm and the effect of exploiting domainspecific knowledge. 1