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principles and practice of constraint programming 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Christian Schulte

ISBN: (数字)9783642406270

ISBN: (纸本)9783642406263

this book constitutes the refereed conference proceedings of the 18th international conference on principles and practice of constraint programming (cp 2013), held in Uppsala, Sweden, in September 2013. the 61 revised papers presented together with 3 invited talks were carefully selected from 138 submissions. the scope of the conference is on all aspects of computing with constraints, including: theory, algorithms, environments, languages, models and systems, applications such as decision making, resource allocation, and agreement technologies.

关键词： Mathematical Logic and Formal Languages Numeric Computing Algorithm Analysis and Problem Complexity Logics and Meanings of Programs Discrete Mathematics in Computer Science programming Languages, Compilers, Interpreters

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Cost-Based Domain Filtering for Stochastic constraint programming

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14th international conference on principles and practice of constraint programming (cp 2008)

作者： Rossi, Roberto Tarim, S. Armagan Hnich, Brahim Prestwich, Steven Univ Coll Cork Constraint Computat Ctr CTVR Cork Ireland Hacettepe Univ Dept Management Ankara Turkey Izmir Univ Econ Fac Comp Sci Izmir Turkey

ISBN: (纸本)9783540859574

Cost based filtering is a novel approach that combines techniques from Operations Research and constraint programming to filter from decision variable domains values that, do not lead to better solutions [7]. Stochastic: constraint programming is a. framework for modeling combinatorial optimization problems that, involve uncertainty [19]. In this work;we show how to perform cost;based filtering for certain classes of stochastic constraint, programs. Our approach is based oil a set of known inequalities borrowed from Stochastic programming - a branch of OR. concerned with modeling and solving problems involving. uncertainty. We discuss bound generation and cost-based domain filtering procedures for a well-known problem in the Stochastic. programming literature, the static stochastic knapsack problem. We also apply our technique to a stochastic sequencing problem. Our results clearly show the value of the proposed approach over;I pure scenario-based Stochastic constraint programming formulation both in terms of explored nodes and run times.

关键词： Costs

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Efficient Implementation of the Global Cardinality constraint with Costs 30

Efficient Implementation of the Global Cardinality Constrain...

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30th international conference on principles and practice of constraint programming, cp 2024

作者： Schmied, Margaux Régin, Jean-Charles Université Côte d'Azur CNRS I3S Sophia Antipolis France

ISBN: (纸本)9783959773362

the success of constraint programming relies partly on the global constraints and implementation of the associated filtering algorithms. Recently, new ideas emerged to improve these implementations in practice, especially regarding the all different constraint. In this paper, we consider the cardinality constraint with costs. the cardinality constraint is a generalization of the all different constraint that specifies the number of times each value must be taken by a given set of variables in a solution. the version with costs introduces an assignment cost and bounds the total sum of assignment costs. the arc consistency filtering algorithm of this constraint is difficult to use in practice, as it systematically searches for many shortest paths. We propose a new approach that works with upper bounds on shortest paths based on landmarks. this approach can be seen as a preprocessing. It is fast and avoids, in practice, a large number of explicit computations of shortest paths. © Margaux Schmied and Jean-Charles Régin.

关键词： Wiener filtering

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Generating Special-Purpose Stateless Propagators for Arbitrary constraints

Generating Special-Purpose Stateless Propagators for Arbitra...

引用

16th Annual international conference on the principles and practice of constraint programming

作者： Gent, Ian P. Jefferson, Chris Miguel, Ian Nightingale, Peter Univ St Andrews Sch Comp Sci St Andrews Fife Scotland

ISBN: (纸本)9783642153952

Given an arbitrary constraint a on 71 variables with domain size d, we show how to generate a custom propagator that establishes GAC in time O(nd) by precomputing the propagation that would be performed on every reachable subdomain of scope(c). Our propagators are stateless: they store no state between calls, and so incur no overhead in storing and backtracking state during search. the preprocessing step can take exponential time and the custom propagator is potentially exponential in size. However, for small constraints used repeatedly, in one problem or many, this technique can provide substantial practical gains. Our experimental results show that, compared with optimised implementations of the table constraint;this technique can lead to an order of magnitude speedup;while doing identical search on realistic problems. the technique can also be many times faster than a decomposition into primitive constraints in the Minion solver. Propagation is so fast that, for constraints available in our solver, the generated propagator compares well with a human-optimised propagator for the same constraint.

关键词： constraint theory

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constraints in Software Testing, Verification and Analysis CSTVA 2013

Constraints in Software Testing, Verification and Analysis C...

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6th IEEE international conference on Software Testing, Verification and Validation (ICST)

作者： Cadar, Cristian Dadeau, Frederic Univ London Imperial Coll Sci Technol & Med South Kensington Campus London SW7 2AZ England INRIA CASSIS FEMTO ST Inst F-25030 Besancon France

ISBN: (纸本)9780769549934;9781479913244

Recent years have seen an increasing interest in the application of constraint solving techniques to test, verify and analyze software systems. A significant body of constraint-based techniques has been proposed and investigated in the context of test input generation, model-based testing, symbolic execution, static analysis, program verification, and many other areas. these techniques use or extend constraint solvers such as SAT and SMT solvers to reason about boolean, integer, real and floating-point data types, as well as complex data structures, control structures, method calls and other program features. the constraint systems that result from this work usually share many common features and are relevant to a variety of application domains. Following a first meeting held with the principles and practice of constraint programming (cp) conference in 2006, and three subsequent meetings at the international conference on Software Testing, Verification and Validation (ICST) in 2010, 2011 and 2012, the aim of this paper is to bring together researchers and practitioners working in constraint-based software testing, verification and analysis, to investigate future developments in this research field.

关键词： constraint handling formal verification program testing

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A k-opt based constraint for the TSP 27

A k-opt based constraint for the TSP

引用

27th international conference on principles and practice of constraint programming, cp 2021

作者： Isoart, Nicolas Régin, Jean-Charles Université Côte d'Azur Nice France

ISBN: (纸本)9783959772112

the LKH algorithm based on k-opt is an extremely efficient algorithm solving the TSP. Given a non-optimal tour in a graph, the idea of k-opt is to iteratively swap k edges of this tour in order to find a shorter tour. However, the optimality of a tour cannot be proved with this method. In that case, exact solving methods such as cp can be used. the cp model is based on a graph variable with mandatory and optional edges. through branch-and-bound and filtering algorithms, the set of mandatory edges will be modified. In this paper, we introduce a new constraint to the cp model named mandatory Hamiltonian path constraint searching for k-opt in the mandatory Hamiltonian paths. Experiments have shown that the mandatory Hamiltonian path constraint allows us to gain on average a factor of 3 on the solving time. In addition, we have been able to solve some instances that remain unsolved with the state of the art cp solver with a 1 week time out. © Nicolas Isoart and Jean-Charles Régin.

关键词： Iterative methods

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Robustness and Stability in constraint programming under Dynamism and Uncertainty

Robustness and Stability in Constraint Programming under Dyn...

引用

20th international conference on the principles and practice of constraint programming (cp)

作者： Climent, Laura Wallace, Richard J. Salido, MiguelA. Barber, Federico Natl Univ Ireland Univ Coll Cork Insight Ctr Data Analyt Cork Ireland Univ Politecn Valencia Inst Automat Informat Ind Madrid Spain

ISBN: (纸本)9783319104287;9783319104270

Because of the dynamism and uncertainty associated with many real life problems, these problems and their associated constraint Satisfaction Problem (CSP) models may change over time; thus an earlier solution found for the latter may become invalid. Moreover, many approaches proposed in the literature cannot be applied when the required information about dynamism is unknown ([9], [4], [5], [11], [10], etc.). this fact has motivated us to consider dynamic situations where, in addition, only limited assumptions about changes can be made. Our analysis focuses on CSPs with ordered and discrete domains that model problems for which the order over the elements of the domain is significant. In these cases, a common type of change that problems may undergo is restrictive modifications over the bounds of the solution space. A discussion of these assumptions, their motivation and real life examples can be found in [3]. In this paper, we present an algorithm that meets the goal of combining solution stability (meaning that solutions can often be repaired using other similar values if they undergo a value loss) and robustness (meaning that solutions have a high likelihood of remaining solutions after changes). the desireability of this combination of features was noted in the survey [8]. Furthermore, in this work we have extended both concepts to apply to the type of CSP analyzed. the paper is organized as follows. Section 2 presents the new conceptions of robustness and stability. Section 3 describes our approach for finding solutions that simultaneously meet both these criteria. In Section 4 we present some experimental results. Section 5 gives conclusions.

关键词： constraint satisfaction problems

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A linear time algorithm for the k-cutset constraint 27

A linear time algorithm for the k-cutset constraint

引用

27th international conference on principles and practice of constraint programming, cp 2021

作者： Isoart, Nicolas Régin, Jean-Charles Université Côte d'Azur Nice France

ISBN: (纸本)9783959772112

In cp, the most efficient model solving the TSP is the Weighted Circuit constraint (WCC) combined with the k-cutset constraint. the WCC is mainly based on the edges cost of a given graph whereas the k-cutset constraint is a structural constraint. Specifically, for each cutset in a graph, the k-cutset constraint imposes that the size of the cutset is greater than or equal to two. In addition, any solution contains an even number of elements from this cutset. Isoart and Régin introduced an algorithm for this constraint. Unfortunately, their approach leads to a time complexity growing with the size of the considered cutsets, i.e. with k. thus, they introduced an algorithm with a quadratic complexity dealing with k lower or equal to three. In this paper, we introduce a linear time algorithm for any k based on a DFS checking the consistency of this constraint and performing its filtering. Experimental results show that the size of most of the k-cutsets is lower or equal than 3. In addition, since the time complexity is improved, our algorithm also improves the solving times. © Nicolas Isoart and Jean-Charles Régin.

关键词： Clustering algorithms

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the Argmax constraint 26th

The Argmax Constraint

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Gange, Graeme Stuckey, Peter J. Monash University Melbourne Australia

ISBN: (纸本)9783030584740

the argmax function returns the index of the (first copy of the) maximum value occuring in a list of values. argmax is important in models where we choose a characteristic value based on a seperate criteria, and for modelling neural networks which make use of argmax in their definition. the argmax constraint has been studied for the special case of its use to find the index of the first true in a list of Booleans, since this is useful for encoding if-then-else chains. Here we examine the general argmax constraint for the first time. We define an efficient domain consistent propagator and a decomposition for integers which implements domain consistency. © 2020, Springer Nature Switzerland AG.

关键词： constraint theory

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Inter-instance nogood learning in constraint programming

Inter-instance nogood learning in constraint programming

引用

18th international conference on principles and practice of constraint programming, cp 2012

作者： Chu, Geoffrey Stuckey, Peter J. National ICT Australia Department of Computer Science and Software Engineering University of Melbourne Australia

ISBN: (纸本)9783642335570

Lazy Clause Generation is a powerful approach to reducing search in constraint programming. this is achieved by recording sets of domain restrictions that previously led to failure as new clausal propagators called nogoods. this dramatically reduces the search and provides orders of magnitude speedups on a wide range of problems. Current implementations of Lazy Clause Generation only allows solvers to learn and utilize nogoods within an individual problem. this means that everything the solver learns will be forgotten as soon as the current problem is finished. In this paper, we show how Lazy Clause Generation can be extended so that nogoods learned from one problem can be retained and used to significantly speed up the solution of other, similar problems. © 2012 Springer-Verlag.

关键词： constraint theory

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