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共 1026 条记录，以下是281-290 订阅

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Tree-Decompositions with Connected Clusters for Solving constraint Networks

Tree-Decompositions with Connected Clusters for Solving Cons...

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

作者： Jegou, Philippe Terrioux, Cyril Aix Marseille Univ LSIS UMR 7296 F-13397 Marseille France

ISBN: (纸本)9783319104287;9783319104270

From a theoretical viewpoint, the (tree-) decomposition methods offer a good approach for solving constraint Satisfaction Problems (CSPs) when their (tree)-width is small. In this case, they have often shown their practical interest. So, the literature (coming from Mathematics or AI) has concentrated its efforts on the minimization of a single parameter, the tree-width. Nevertheless, experimental studies have shown that this parameter is not always the most relevant to consider for solving CSPs. In this paper, we experimentally show that the decomposition algorithms of the state of the art produce clusters (a tree-decomposition is a tree of clusters) having several connected components. then we highlight that such clusters create a real problem for the efficiency of solving methods. To avoid this kind of problem, we consider here a new kind of graph decomposition called Bag-Connected Tree-Decomposition, which considers only tree-decompositions such that each cluster is connected. We propose a first polynomial time algorithm to find such decompositions. Finally, we show experimentally that using these bag-connected tree-decompositions improves significantly the solving of CSPs by decomposition methods.

关键词： Trees (mathematics)

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the Non-overlapping constraint between Objects Described by Non-linear Inequalities

The Non-overlapping Constraint between Objects Described by ...

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

作者： Salas, Ignacio Chabert, Gilles Goldsztejn, Alexandre Mines Nantes LINA UMR 6241 Nantes France CNRS LINA UMR 6241 F-75700 Paris France

ISBN: (纸本)9783319104287;9783319104270

Packing 2D objects in a limited space is an ubiquitous problem with many academic and industrial variants. In any case, solving this problem requires the ability to determine where a first object can be placed so that it does not intersect a second, previously placed, object. this subproblem is called the non-overlapping constraint. the complexity of this non-overlapping constraint depends on the type of objects considered. It is simple in the case of rectangles. It has also been studied in the case of polygons. this paper proposes a numerical approach for the wide class of objects described by non-linear inequalities. Our goal here is to calculate the non-overlapping constraint, that is, to describe the set of all positions and orientations that can be assigned to the first object so that intersection with the second one is empty. this is done using a dedicated branch & prune approach. We first show that the non-overlapping constraint can be cast into a Minkowski sum, even if we take into account orientation. We derive from this an inner contractor, that is, an operator that removes from the current domain a subset of positions and orientations that necessarily violate the non-overlapping constraint. this inner contractor is then embedded in a sweeping loop, a pruning technique that was only used with discrete domains so far. We finally come up with a branch & prune algorithm that outperforms Rsolver, a generic state-of-the-art solver for continuous quantified constraints.

关键词： Contractors

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Worst-Case Scheduling of Software Tasks A constraint Optimization Model to Support Performance Testing

Worst-Case Scheduling of Software Tasks A Constraint Optimiz...

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

作者： Di Alesio, Stefano Nejati, Shiva Briand, Lionel Gotlieb, Arnaud Simula Res Lab Certus Ctr Software Verificat & Validat Oslo Norway Univ Luxembourg Interdisciplinary Ctr Reliabil Secur & Trust SnT Luxembourg Luxembourg

ISBN: (纸本)9783319104287;9783319104270

Real-Time Embedded Systems (RTES) in safety-critical domains, such as maritime and energy, must satisfy strict performance requirements to be deemed safe. therefore, such systems have to be thoroughly tested to ensure their correct behavior even under the worst operating conditions. In this paper, we address the need of deriving worst case scenarios with respect to three common performance requirements, namely task deadlines, response time, and CPU usage. Specifically, we investigate whether this worst-case analysis can be effectively re-expressed as a Constrained Optimization Problem (COP) over the space of possible inputs to the system. Solving this problem means finding the sets of inputs that maximize the chance to violate performance requirements at runtime. Such inputs can in turn be used to test if the target RTES meets the expected performance even in the worst case. We develop an OPL model for IBM ILOG CP OPTIMIZER that implements a task priority-based preemptive scheduling, and apply it to a case study from the maritime and energy domain. Our validation shows that (1) the input to our model can be provided with reasonable effort in an industrial setting, and (2) the COP effectively identifies test cases that maximize deadline misses, response time, and CPU usage.

关键词： Constrained optimization

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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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Computing a Payoff Division in the Least Core for MC-nets Coalitional Games 1

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17th international conference on principles and practice of Multi-Agent Systems (PRIMA)

作者： Hirayama, Katsutoshi Hanada, Kenta Ueda, Suguru Yokoo, Makoto Iwasaki, Atsushi Kobe Univ Kobe Hyogo Japan Natl Inst Informat Kumamoto Japan Kyushu Univ Fukuoka Japan Univ Elect Commnunicat Tokyo Japan

ISBN: (数字)9783319131917

ISBN: (纸本)9783319131917;9783319131900

MC-nets is a concise representation of the characteristic functions that exploits a set of rules to compute payoffs. Given a MC-nets instance, the problem of computing a payoff division in the least core, which is a generalization of the core-non-emptiness problem that is known to be coNP-complete, is definitely a hard computational problem. In fact, to the best of our knowledge, no algorithm can actually compute such a payoff division for MC-nets instances with dozens of agents. We propose a new algorithm for this problem, that exploits the constraint generation technique to solve the linear programming problem that potentially has a huge number of constraints. Our experimental results are striking since, using 8 GB memory, our proposed algorithm can successfully compute a payoff division in the least core for the instances with up to 100 agents, but the naive algorithm fails due to a lack of memory for instances with 30 or more agents.

关键词： coalitional games least core MC-nets constraint generation

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A complete solver for constraint games

A complete solver for constraint games

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20th international conference on the principles and practice of constraint programming, CP 2014

作者： Nguyen, thi-Van-Anh Lallouet, Arnaud GREYC Université de Caen Campus Côte de Nacre Boulevard du Maréchal Juin BP 5186 14032 Caen Cedex France

ISBN: (纸本)9783319104270

Game theory studies situations in which multiple agents having conflicting objectives have to reach a collective decision. the question of a compact representation language for agents utility function is of crucial importance since the classical representation of a n-players game is given by a n-dimensional matrix of exponential size for each player. In this paper we use the framework of constraint Games in which CSP are used to represent utilities. constraint programming -including global constraints- allows to easily give a compact and elegant model to many useful games. constraint Games come in two flavors: constraint Satisfaction Games and constraint Optimization Games, the first one using satisfaction to define boolean utilities. In addition to multimatrix games, it is also possible to model more complex games where hard constraints forbid certain situations. In this paper we study complete search techniques and show that our solver using the compact representation of constraint Games is faster than the classical game solver Gambit by one to two orders of magnitude. © 2014 Springer international Publishing Switzerland.

关键词： Constrained optimization

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the balance constraint family

The balance constraint family

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20th international conference on the principles and practice of constraint programming, CP 2014

作者： Bessiere, Christian Hebrard, Emmanuel Katsirelos, George Kiziltan, Zeynep Picard-Cantin, Émilie Quimper, Claude-Guy Walsh, Toby CNRS University of Montpellier France LAAS-CNRS Toulouse France INRA Toulouse France DISI University of Bologna Italy Université Laval Canada NICTA University of New South Wales Australia

ISBN: (纸本)9783319104270

the Balance constraint introduced by Beldiceanu ensures solutions are balanced. this is useful when, for example, there is a requirement for solutions to be fair. Balance bounds the difference B between the minimum and maximum number of occurrences of the values assigned to the variables. We show that achieving domain consistency on Balance is NP-hard. We therefore introduce a variant, AllBalance with a similar semantics that is only polynomial to propagate. We consider various forms of AllBalance and focus on AtMostallBalance which achieves what is usually the main goal, namely constraining the upper bound on B. We provide a specialized propagation algorithm, and a powerful decomposition both of which run in low polynomial time. Experimental results demonstrate the promise of these new filtering methods. © 2014 Springer international Publishing Switzerland.

关键词： Polynomial approximation

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Automatically improving constraint models in savile row through associative-commutative common subexpression elimination

Automatically improving constraint models in savile row thro...

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20th international conference on the principles and practice of constraint programming, CP 2014

作者： Nightingale, Peter Akgün, Özgür Gent, Ian P. Jefferson, Christopher Miguel, Ian School of Computer Science University of St. Andrews St.-Andrews Fife-KY16 9SX United Kingdom

ISBN: (纸本)9783319104270

When solving a problem using constraint programming, constraint modelling is widely acknowledged as an important and difficult task. Even a constraint modelling expert may explore many models and spend considerable time modelling a single problem. therefore any automated assistance in the area of constraint modelling is valuable. Common sub-expression elimination (CSE) is a type of constraint reformulation that has proved to be useful on a range of problems. In this paper we demonstrate the value of an extension of CSE called Associative-Commutative CSE (AC-CSE). this technique exploits the properties of associativity and commutativity of binary operators, for example in sum constraints. We present a new algorithm, X-CSE, that is able to choose from a larger palette of common subexpressions than previous approaches. We demonstrate substantial gains in performance using X-CSE. For example on BIBD we observed speed increases of more than 20 times compared to a standard model and that using X-CSE outperforms a sophisticated model from the literature. For Killer Sudoku we found that X-CSE can render some apparently difficult instances almost trivial to solve, and we observe speed increases up to 350 times. For BIBD and Killer Sudoku the common subexpressions are not present in the initial model: an important part of our methodology is reformulations at the preprocessing stage, to create the common subexpressions for X-CSE to exploit. In summary we show that X-CSE, combined with preprocessing and other reformulations, is a powerful technique for automated modelling of problems containing associative and commutative constraints. © 2014 Springer international Publishing Switzerland.

关键词： Problem solving

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principles and practice of constraint programming - 18th international conference, CP 2012, Proceedings

Principles and Practice of Constraint Programming - 18th Int...

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

ISBN: (纸本)9783642335570

the proceedings contain 71 papers. the topics discussed include: constraint programming and a usability quest;optimization challenges in smart grid operations;where are the interesting problems?;a generic method for identifying and exploiting dominance relations;scheduling scientific experiments on the Rosetta/Philae mission;an optimal arc consistency algorithm for a chain of atmost constraints with cardinality;conflict directed lazy decomposition;boosting local consistency algorithms over floating-point numbers;a model seeker: extracting global constraint models from positive examples;on computing minimal equivalent subformulas;Weibull-based benchmarks for bin packing;space-time tradeoffs for the regular constraint;inter-instance nogood learning in constraint programming;a characterization of the complexity of forbidding subproblems in binary max-CSP;and optimization modeling for software developers.

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Efficient pseudorecursive evaluation schemes for non-adaptive sparse grids 1

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2nd Workshop on Sparse Grids and Applications, SGA 2012

作者： Buse, Gerrit Pflüger, Dirk Jacob, Riko TU München München Germany Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany ETH Zurich Zurich Switzerland

ISBN: (数字)9783319045375

ISBN: (纸本)9783319045368

In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (Proceedings of the 16th ACM Symposium on principles and practice of Parallel programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (Proceedings of the international conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation. © Springer international Publishing Switzerland 2014.

关键词： Parallel programming

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