Relevant bibliographies by topics / Weighted constraint satisfaction problem

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Weighted constraint satisfaction problem'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Weighted constraint satisfaction problem"

1

Gallardo, J. E., C. Cotta, and A. J. Fernández. "Solving Weighted Constraint Satisfaction Problems with Memetic/Exact Hybrid Algorithms." Journal of Artificial Intelligence Research 35 (July 28, 2009): 533–55. http://dx.doi.org/10.1613/jair.2770.

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A weighted constraint satisfaction problem (WCSP) is a constraint satisfaction problem in which preferences among solutions can be expressed. Bucket elimination is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply bucket elimination is too high, a heuristic method based on it (denominated mini-buckets) can be used to calculate bounds for the optimal solution. Nevertheless, the curse of dimensionality makes these techniques impractical on large scale problems. In response to this situation, we present a memetic algorithm
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Tay, Noel Nuo Wi, János Botzheim, and Naoyuki Kubota. "Weighted Constraint Satisfaction for Smart Home Automation and Optimization." Advances in Artificial Intelligence 2016 (November 23, 2016): 1–15. http://dx.doi.org/10.1155/2016/2959508.

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Automation of the smart home binds together services of hardware and software to provide support for its human inhabitants. The rise of web technologies offers applicable concepts and technologies for service composition that can be exploited for automated planning of the smart home, which can be further enhanced by implementation based on service oriented architecture (SOA). SOA supports loose coupling and late binding of devices, enabling a more declarative approach in defining services and simplifying home configurations. One such declarative approach is to represent and solve automated pla
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Nguyen, Thi Hong Hiep, Thomas Schiex, and Christian Bessiere. "Strong consistencies for weighted constraint satisfaction problems." Constraints 20, no. 4 (2015): 471–72. http://dx.doi.org/10.1007/s10601-015-9208-8.

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Zytnicki, M., C. Gaspin, S. De Givry, and T. Schiex. "Bounds Arc Consistency for Weighted CSPs." Journal of Artificial Intelligence Research 35 (July 30, 2009): 593–621. http://dx.doi.org/10.1613/jair.2797.

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The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to various problems, including resource allocation, bioinformatics, scheduling, etc. To solve such problems, solvers usually rely on branch-and-bound algorithms equipped with local consistency filtering, mostly soft arc consistency. However, these techniques are not well suited to solve problems with very large domains. Motivated by the resolution of an RNA gene localization problem inside large genomic sequences, and in
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Yamakami, Tomoyuki. "Constant Unary Constraints and Symmetric Real-Weighted Counting Constraint Satisfaction Problems." Theory of Computing Systems 55, no. 1 (2013): 170–201. http://dx.doi.org/10.1007/s00224-013-9518-4.

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Nonobe, Koji, and Toshihide Ibaraki. "An Improved Tabu Search Method For The Weighted Constraint Satisfaction Problem." INFOR: Information Systems and Operational Research 39, no. 1 (2001): 131–51. http://dx.doi.org/10.1080/03155986.2001.11732431.

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Law, Yat Chiu, Jimmy H. M. Lee, and May H. C. Woo. "Redundant modeling in permutation weighted constraint satisfaction problems." Constraints 15, no. 3 (2009): 354–403. http://dx.doi.org/10.1007/s10601-009-9075-2.

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Lee, J. H. M., and K. L. Leung. "Consistency Techniques for Flow-Based Projection-Safe Global Cost Functions in Weighted Constraint Satisfaction." Journal of Artificial Intelligence Research 43 (February 28, 2012): 257–92. http://dx.doi.org/10.1613/jair.3476.

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Many combinatorial problems deal with preferences and violations, the goal of which is to find solutions with the minimum cost. Weighted constraint satisfaction is a framework for modeling such problems, which consists of a set of cost functions to measure the degree of violation or preferences of different combinations of variable assignments. Typical solution methods for weighted constraint satisfaction problems (WCSPs) are based on branch-and-bound search, which are made practical through the use of powerful consistency techniques such as AC*, FDAC*, EDAC* to deduce hidden cost information
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Alaoui, Mohammed El, Karim El moutaouakil, and Mohamed Ettaouil. "Weighted Constraint Satisfaction and Genetic Algorithm to Solve the View Selection Problem." International Journal of Database Management Systems 9, no. 4 (2017): 11–20. http://dx.doi.org/10.5121/ijdms.2017.9402.

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Yamakami, Tomoyuki. "Approximate counting for complex-weighted Boolean constraint satisfaction problems." Information and Computation 219 (October 2012): 17–38. http://dx.doi.org/10.1016/j.ic.2012.08.002.

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Dissertations / Theses on the topic "Weighted constraint satisfaction problem"

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Black, Daniel Peter. "Search in weighted constraint satisfaction problems." Thesis, University of Leeds, 2003. http://etheses.whiterose.ac.uk/1309/.

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A wide variety of real-world optimisation problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs). Such problems are NP-hard and require an exponential amount of time to find the optimal solution. This thesis concentrates on the University Examination Timetabling Problem. A general abstraction of this problem has been used, as there are many institution-specific rules which could be incorporated into the problem. The use of this problem type allows WCSPs to be investigated using realistic problem data and allows a comparison with previously published results for the probl
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Nguyen, Thi Hong Hiep. "Strong consistencies for weighted constraint satisfaction problems." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30004/document.

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Cette thèse se focalise sur l'étude de cohérences locales fortes afin de résoudre des problèmes d'optimisation sur des réseaux de fonctions de coûts (ou réseaux de contraintes pondérées). Ces méthodes fournissent le minorant nécessaire pour des approches de type "Séparation-Evaluation". Nous étudions dans un premier temps la cohérence d'Arc virtuelle (VAC), une des plus fortes cohérences d'arcs du domaine, qui est établie via l'établissement de la cohérence d'arc dure dans une séquence de réseaux de contraintes classiques. L'algorithme itératif pour établir VAC est amélioré via l'introduction
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Paris, Nicolas. "Intégration de techniques CSP pour la résolution du problème WCSP." Thesis, Artois, 2014. http://www.theses.fr/2014ARTO0405/document.

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Cette thèse se situe dans le contexte de la programmation par contraintes (CP). Plus précisément, nous nous sommes intéressés au problème de satisfaction de contraintes pondérées (WCSP). De nombreuses approches ont été proposées pour traiter ce problème d’optimisation. Les méthodes les plus efficaces utilisent des cohérences locales souples sophistiquées comme par exemple la cohérence d’arc directionnelle complète FDAC∗, la cohérence d’arc directionnelle existentielle EDAC∗, etc. Établies grâce à des opérations de transferts de coût préservant l’équivalence des réseaux, l’utilisation de ces co
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Fulla, Peter. "On the valued constraint satisfaction problem." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:bb2491ef-d802-4c5d-a388-a042644a4b47.

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The Valued Constraint Satisfaction Problem (VCSP) is a framework which captures many natural decision and optimisation problems. An instance of the VCSP consists of a set of variables, which are to be assigned labels from a finite domain, and a collection of local constraints, each specified by a weighted relation mapping labellings of the variables in the constraint's scope to values. The objective is to minimise the total value from all constraints. The VCSP is commonly parameterised by a language, i.e. a set of weighted relations that are available for use in the constraints. Languages are
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Nightingale, Peter. "Consistency and the quantified constraint satisfaction problem /." St Andrews, 2007. http://hdl.handle.net/10023/759.

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Nightingale, Peter William. "Consistency and the Quantified Constraint Satisfaction Problem". Thesis, University of St Andrews, 2007. http://hdl.handle.net/10023/759.

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Constraint satisfaction is a very well studied and fundamental artificial intelligence technique. Various forms of knowledge can be represented with constraints, and reasoning techniques from disparate fields can be encapsulated within constraint reasoning algorithms. However, problems involving uncertainty, or which have an adversarial nature (for example, games), are difficult to express and solve in the classical constraint satisfaction problem. This thesis is concerned with an extension to the classical problem: the Quantified Constraint Satisfaction Problem (QCSP). QCSP has recently attra
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Zhang, Lixi. "Solving the timetabling problem using constraint satisfaction programming." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20051104.155838/index.html.

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Powell, Robert David. "Complexity classifications for the valued constraint satisfaction problem." Thesis, Durham University, 2016. http://etheses.dur.ac.uk/11485/.

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In a valued constraint satisfaction problem (VCSP), the goal is to find an assignment of values to variables that minimizes a given sum of functions. Each function in the sum depends on a subset of variables, takes values which are rational numbers or infinity, and is chosen from a fixed finite set of functions called a constraint language. We study how the computational complexity of this problem depends on the constraint language. We often consider the case where infinite values are disallowed, and refer to such constraint languages as being finite-valued. If we consider such finite-valued c
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Andersson, Jakob. "Automatic Invoice Data Extraction as a Constraint Satisfaction Problem." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411596.

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Invoice processing has traditionally been heavily dependent onmanual labor, where the task is to identify and move certaininformation from an origin to a destination. A time demandingtask with a high interest of automation to reduce time ofexecution, fault-risk and cost.With the evergrowing interest in automation and ArtificialIntelligence (AI), this thesis will explore the possibilities ofautomating the task of extracting and mapping information ofinterest by defining the problem as a Constraint OptimizationProblem (COP) using numeric relations between present information.The problem is then
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Magaji, Amina Sambo-Muhammad. "Combining search strategies for distributed constraint satisfaction." Thesis, Robert Gordon University, 2015. http://hdl.handle.net/10059/1374.

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Many real-life problems such as distributed meeting scheduling, mobile frequency allocation and resource allocation can be solved using multi-agent paradigms. Distributed constraint satisfaction problems (DisCSPs) is a framework for describing such problems in terms of related subproblems, called a complex local problem (CLP), which are dispersed over a number of locations, each with its own constraints on the values their variables can take. An agent knows the variables in its CLP plus the variables (and their current value) which are directly related to one of its own variables and the const
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Books on the topic "Weighted constraint satisfaction problem"

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Artificial intelligence: A modern approach. 2nd ed. Prentice Hall, 2003.

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Peter, Norvig, ed. Artificial intelligence: A modern approach. 2nd ed. Prentice Hall/Pearson Education, 2003.

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Peter, Norvig, ed. Artificial intelligence: A modern approach. Prentice Hall, 1995.

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Norvig, Peter. Artificial Intelligence: A Modern Approach. Pearson Education, Limited, 1994.

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Artificial intelligence: A Modern Approach. Prentice Hall, 2010.

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Norvig, Peter. Artificial Intelligence: A Modern Approach. Pearson, 2020.

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Artificial intelligence: A Modern Approach. Prentice Hall, 2010.

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Artificial Intelligence: A Modern Approach. Pearson, 2015.

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Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach. Pearson Education, Limited, 2010.

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Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach (2nd Edition). 2nd ed. Prentice Hall, 2002.

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Book chapters on the topic "Weighted constraint satisfaction problem"

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Yamakami, Tomoyuki. "Approximate Counting for Complex-Weighted Boolean Constraint Satisfaction Problems." In Approximation and Online Algorithms. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18318-8_23.

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Yamakami, Tomoyuki. "Approximation Complexity of Complex-Weighted Degree-Two Counting Constraint Satisfaction Problems." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22685-4_11.

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Yokoo, Makoto. "Constraint Satisfaction Problem." In Distributed Constraint Satisfaction. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59546-2_1.

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Yokoo, Makoto. "Distributed Constraint Satisfaction Problem." In Distributed Constraint Satisfaction. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59546-2_2.

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Miguel, Ian. "The Constraint Satisfaction Problem." In Dynamic Flexible Constraint Satisfaction and its Application to AI Planning. Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-378-7_2.

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de Givry, Simon, and George Katsirelos. "Clique Cuts in Weighted Constraint Satisfaction." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66158-2_7.

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Paredis, Jan. "Co-evolutionary constraint satisfaction." In Parallel Problem Solving from Nature — PPSN III. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58484-6_249.

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Madelaine, Florent, and Stéphane Secouard. "Quantified Valued Constraint Satisfaction Problem." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98334-9_20.

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Hirayama, Katsutoshi, and Makoto Yokoo. "Distributed partial constraint satisfaction problem." In Principles and Practice of Constraint Programming-CP97. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0017442.

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Udovićić, Mirna. "Constraint Satisfaction Problem: Professor Weekly Schedule." In Lecture Notes in Networks and Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71321-2_27.

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Conference papers on the topic "Weighted constraint satisfaction problem"

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Matsuda, M., Y. Makino, Y. Nakama, and T. Nishimura. "Shipbuilding Scheduling Problems Solved by Algorithms as a Weighted Constraint Satisfaction Problem." In International Conference on Computer Applications in Shipbuilding. RINA, 2007. http://dx.doi.org/10.3940/rina.iccas.2007.54.

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"Modeling and Algorithm for Dynamic Multi-objective Weighted Constraint Satisfaction Problem." In International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004816704200427.

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Lee, Jimmy H. M., Terrence W. K. Mak, and Justin Yip. "Weighted Constraint Satisfaction Problems with Min-Max Quantifiers." In 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2011. http://dx.doi.org/10.1109/ictai.2011.121.

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Bidar, Mahdi, and Malek Mouhoub. "Solving Weighted Constraint Satisfaction Problems Using a new Self-Adaptive Discrete Firefly Algorithm." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914624.

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Furuya, Hiroki, Nagao Ogino, Satoshi Konishi, et al. "An Optimal Route Computation Method for GMPLS Based Survivable Network with a Tabu Search Algorithm for the Weighted Constraint Satisfaction Problem." In Networks 2006. 12th International Telecommunications Network Strategy and Planning Symposium. IEEE, 2006. http://dx.doi.org/10.1109/netwks.2006.300373.

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Takaci, Aleksandar, Srdjan Skrbic, and Aleksandar Perovic. "Generalised Prioritised Fuzzy Constraint Satisfaction Problem." In 2009 7th International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2009. http://dx.doi.org/10.1109/sisy.2009.5291177.

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Zhuk, Dmitriy. "An Algorithm for Constraint Satisfaction Problem." In 2017 IEEE 47th International Symposium on Multiple-Valued Logic (ISMVL). IEEE, 2017. http://dx.doi.org/10.1109/ismvl.2017.20.

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Zhuk, Dmitriy. "No-Rainbow Problem and the Surjective Constraint Satisfaction Problem." In 2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS). IEEE, 2021. http://dx.doi.org/10.1109/lics52264.2021.9470632.

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Mortazavi, Reza, and Saeed Jalili. "Iterative constraint satisfaction method for microaggregation problem." In 2014 11th International ISC Conference on Information Security and Cryptology (ISCISC). IEEE, 2014. http://dx.doi.org/10.1109/iscisc.2014.6994048.

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Dirakkhunakon, Sipang, and Yoothana Suansook. "Stochastic Search Algorithm for Constraint Satisfaction Problem." In 2008 International Conference on Computer and Electrical Engineering (ICCEE). IEEE, 2008. http://dx.doi.org/10.1109/iccee.2008.85.

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Reports on the topic "Weighted constraint satisfaction problem"

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Sadeh, Norman, Katia Sycara, and Yalin Xiong. Backtracking Techniques for the Job Shop Scheduling Constraint Satisfaction Problem. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada289435.

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Sadeh, Norman M., and Mark S. Fox. Variable and Value Ordering Heuristics for the Job Shop Scheduling Constraint Satisfaction Problem. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada311303.

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