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共 323 条记录，以下是211-220 订阅

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Discriminating Instance Generation for Automated constraint Model Selection

Discriminating Instance Generation for Automated Constraint ...

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

作者： Gent, Ian P. Hussain, Bilal Syed Jefferson, Christopher Kotthoff, Lars Miguel, Ian Nightingale, Glenna F. Nightingale, Peter Univ St Andrews Sch Comp Sci St Andrews KY16 9AJ Fife Scotland INSIGHT Ctr Data Analyt Dublin Ireland

ISBN: (纸本)9783319104287;9783319104270

One approach to automated constraint modelling is to generate, and then select from, a set of candidate models. this method is used by the automated modelling system CONJURE. To select a preferred model or set of models for a problem class from the candidates CONJURE produces, we use a set of training instances drawn from the target class. It is important that the training instances are discriminating. If all models solve a given instance in a trivial amount of time, or if no models solve it in the time available, then the instance is not useful for model selection. this paper addresses the task of generating small sets of discriminating training instances automatically. the instance space is determined by the parameters of the associated problem class. We develop a number of methods of finding parameter configurations that give discriminating training instances, some of them leveraging existing parameter-tuning techniques. Our experimental results confirm the success of our approach in reducing a large set of input models to a small set that we can expect to perform well for the given problem class.

关键词： Automation

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constraint programming and a usability quest

Constraint programming and a usability quest

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

作者： Michel, Laurent D. University of Connecticut Storrs CT 06269-2155 United States

ISBN: (纸本)9783642335570

In 2004, Jean-Francois Puget presented [2] an analysis of the "simplicity of Use" of constraint programming from which he articulated a series of challenges to make constraint programming systems accessible and easier to use. the core of the argument was a contrast between mathematical programming and constraint programming tools. Mathematical programming adopts a model and run paradigm, rely on a simple vocabulary to model problems (i.e., linear constraints), support standard formats for sharing models and benefit from extensive documentation on how to model [5]. constraint programming features a model and search paradigm, rich modeling languages with combinatorial objects and has a distinctive flavor of programming. While it can be construed as cp's Achilles' heel, it is also its most potent strength and is supported by modeling aids [3,4]. the very existence of sophisticated parameter tuning solutions for SAT solvers and Math programming solvers to determine ideal parameters (e.g., ParamILS [1]) certainly cast a major shadow on the potency of the model and run mantra that is evolving into model and search for the right parameters. © 2012 Springer-Verlag.

关键词： constraint programming

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Automated Symmetry Breaking and Model Selection in CONJURE

Automated Symmetry Breaking and Model Selection in CONJURE

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19th Annual international conference on principles and practice of constraint programming (cp)

作者： Akgun, Ozgur Frisch, Alan M. Gent, Ian P. Hussain, Bilal Syed Jefferson, Christopher Kotthoff, Lars Miguel, Ian Nightingale, Peter Univ St Andrews St Andrews KY16 9AJ Fife Scotland Univ York York YO10 5DD N Yorkshire England Cork Constraint Computat Ctr Cork Ireland

ISBN: (纸本)9783642406263;9783642406270

constraint modelling is widely recognised as a key bottleneck in applying constraint solving to a problem of interest. the CONJURE automated constraint modelling system addresses this problem by automatically refining constraint models from problem specifications written in the ESSENCE language. ESSENCE provides familiar mathematical concepts like sets, functions and relations nested to any depth. To date, CONJURE has been able to produce a set of alternative model kernels (i.e. without advanced features such as symmetry breaking or implied constraints) for a given specification. the first contribution of this paper is a method by which CONJURE can break symmetry in a model as it is introduced by the modelling process. this works at the problem class level, rather than just individual instances, and does not require an expensive detection step after the model has been formulated. this allows CONJURE to produce a higher quality set of models. A further limitation of CONJURE has been the lack of a mechanism to select among the models it produces. the second contribution of this paper is to present two such mechanisms, allowing effective models to be chosen automatically.

关键词： Specifications

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the offshore resources scheduling problem: Detailing a constraint programming approach

The offshore resources scheduling problem: Detailing a const...

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

作者： Serra, thiago Nishioka, Gilberto Marcellino, Fernando J. M. PETROBRAS - Petróleo Brasileiro S.A. Avenida Paulista 901 São Paulo SP 01311-100 Brazil

ISBN: (纸本)9783642335570

the development of maritime oil wells depends on the availability of specialized fleet capable of performing the required activities. In addition, the exploitation of each well can only start when it is connected through pipes to a producing unit. the Offshore Resources Scheduling Problem (ORSP) combines such restrictions with the aim to prioritize development projects of higher return in oil production. In this work, an extended description of the ORSP is tackled with constraint programming (cp). Such extension refers to the customization of pipes and to the scheduling of fleet maintenance periods. the use of cp is due to the noted ability of the technique to model and solve large and complex scheduling problems. For the type of scenarios faced by Petrobras, the reported approach was able to quickly deliver good-quality solutions. © 2012 Springer-Verlag.

关键词： Scheduling

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Structural Tractability of Propagated constraints

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

作者： Green, Martin J. Jefferson, Christopher Univ London Dept Comp Sci London WC1E 7HU England Univ Oxford Comp Lab Oxford OX1 2JD England

ISBN: (纸本)9783540859574

Modern constraint solvers do trot require constraints to l), represented using ally particular data structure. Instead, constraints rue given as black boxes known as propagators. Propagators are given a. list of current domains for variables and are :allowed to prune values not. consistent with these current domains. Using propagation as the only primitive operation on constraints imposes restrictions on the operations that can be performed in polynomial time. In the extensional representation of constraints (so-called positive table constraints) join and project are primitive polynomial-time operations. this is not true for propagated constraints. the question we pose ill this paper is: If propagation is the only primitive operation, what are: the: structurally tractable classes of constraint programs (whose instances can he solved in polynomial time)? We consider a hierarchy of propagators: arbitrary propagators, whose only ability is consistency checking;partial assignment membership propagators, which allow us to check partial assignments;and generalised arc consistency propagators, the strongest, form of propagator. In the first two cases, we answer the posed question by establishing dichotomies. In the case of generalised are consistency propagators, we achieve a useful dichotomy in the restricted case: of acyclic structures.

关键词： Polynomial approximation

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Operations research and constraint programming at google 17th

Operations research and constraint programming at google

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17th international conference on principles and practice of constraint programming, cp 2011

作者： Perron, Laurent Google SA 38 avenue de l’opéra Paris75002 France

ISBN: (纸本)9783642237850

the Operations Research and Optimization team at Google develops both general purpose optimization tools and solutions for internal optimization problems. We will describe the tools – most of which are available at http://***/p/or-tools – and present a few applications, for example in the area of assigning jobs to machines. Furthermore, we will discuss our usage of constraint programming in greater detail, and how it fits into the general usage of Operations Research at Google. Finally, we will also share our future plans. © 2011, Springer-Verlag Berlin Heidelberg.

关键词： Operations research

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Robustness and Stability in constraint programming under Dynamism and Uncertainty

Robustness and Stability in Constraint Programming under Dyn...

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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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Coalition Structure Generation Utilizing Compact Characteristic Function Representations

Coalition Structure Generation Utilizing Compact Characteris...

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15th international conference on principles and practice of constraint programming (cp 2009)

作者： Ohta, Naoki Conitzer, Vincent Ichimura, Ro Sakurai, Yuko Iwasaki, Atsushi Yokoo, Makoto Kyushu Univ Dept ISEE Fukuoka 8190395 Japan Duke Univ Dept Comp Sci Durham NC USA

ISBN: (纸本)9783642042430

this paper presents a, new way of formalizing the Coalition Structure Generation problem (CSG), so that we can apply constraint optimization techniques to it. Forming effective coalitions is a major research challenge in AI and of multi-agent systems. CSG involves partitioning a. set of agents into coalitions so that social surplus is maximized. Traditionally, the input of the CSG problem is a, black-box function called a, which takes a, coalition as an input and returns the value of the coalition. As a, result, applying constraint optimization techniques to this problem has been feasible. However, characteristic functions that appear in practice often can lie represented concisely by a set of rules, rather than a single black-box function. then, we can solve the CSG problem more efficiently by applying constraint optimization techniques to the compact;representation directly. We present;new formalizations of the CSG problem by utilizing recently developed compact representation schemes for characteristic functions. We first characterize the complexity of the CSG under these representation schemes. In this context, the complexity is driven more by the number of rules rather than by the number of agents. Furthermore, as an initial step towards developing efficient constraint optimization algorithms for solving the CSG problem, we develop mixed integer programming formulations and show that an off-the-shelf optimization package can perform reasonably well, i.e., it can solve instances with a few hundred agents, while the state-of-the-art algorithm (which does not make use of compact representations) can solve instances with up to 27 agents.

关键词： Multiagent systems coalition structure generation constraint optimization

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Heuristic constraint propagation 8th

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8th international conference on principles and practice of constraint programming, cp 2002

作者： Sellman, Meinolf Harvey, Warwick University of Paderborn Department of Mathematics and Computer Science Fürstenallee 11 PaderbornD-33102 Germany IC-Parc Imperial College Exhibition Road LondonSW7 2AZ United Kingdom

ISBN: (纸本)3540441204

For NP-hard constraint satisfaction problems the existence of a feasible solution cannot be decided efficiently. Applying a tree search often results in the exploration of parts of the search space that do not contain feasible solutions at all. Redundant constraints can help to detect inconsistencies of partial assignments higher up in the search tree. Using the social golfer problem as an example we show how complex redundant constraints can be propagated incompletely using local search heuristics. © Springer-Verlag Berlin Heidelberg 2002.

关键词： constraint satisfaction problems

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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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