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Meseguer, Pedro; Bouhmala, Noureddine; Bouzoubaa, Taoufik; Irgens, Morten; Sánchez, Martí

doi:10.1023/a:1021902812784

Cited by 22 publications

(4 citation statements)

References 49 publications

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“…Weighted constraint satisfaction approaches (Lau 2002) weight the constraints with positive integers and maximize the objective of constraint satisfaction. Review of constraint satisfaction approaches (Meseguer et al 2003) and solution methods (Miguel and Shen 2001) indicate their advantages over other methods in solving over-constrained formulations. Target vector approaches (Coello 2001) are conceptually similar to PCS formulations.…”

Section: Partial Constraint Satisfaction Approachesmentioning

confidence: 99%

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Ferreira¹,

Teegavarapu²

2012

Engineering Optimization

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Optimal operation models for a hydropower system using partial constraint satisfaction (PCS) approaches are proposed and developed in this study. The models use mixed integer nonlinear programming (MINLP) formulations with binary variables. The models also integrate a turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream water quality impairment. New PCS-based models for hydropower optimization formulations are developed using binary and continuous evaluator functions to maximize the constraint satisfaction. The models are applied to a reallife hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to solve the optimization formulations. Decision maker's preferences towards power production targets and water quality improvements are incorporated using partial satisfaction constraints to obtain compromise operating rules for a multi-objective reservoir operation problem dominated by conflicting goals of energy production, water quality and consumptive water uses.

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Section: Partial Constraint Satisfaction Approachesmentioning

confidence: 99%

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Ferreira¹,

Teegavarapu²

2012

Engineering Optimization

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“…The basic idea of such a hierarchy is that constraints are separated into multiple levels, and constraints of a higher level are always to be preferentially satisfied over those of a lower level. The notion of such hierarchies, also known as "prioritised constraints", has been extensively studied in the area of artificial intelligence and the constraint satisfaction approach to solving combinatorial optimisation problems, see for example (Dubois et al 1996;Meseguer et al 2003;Henz et al 2004;Callennec and Boulic 2004). As an example, from Borning et al (1987) …”

Section: Framework For Evaluation Of Solutionsmentioning

confidence: 99%

A new model for automated examination timetabling

et al. 2011

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Automated examination timetabling has been addressed by a wide variety of methodologies and techniques over the last ten years or so. Many of the methods in this broad range of approaches have been evaluated on a collection of benchmark instances provided at the University of Toronto in 1996. Whilst the existence of these datasets has provided an invaluable resource for research into examination timetabling, the instances have significant limitations in terms of their relevance to real-world examination timetabling in modern universities. This paper presents a detailed model which draws upon experiences of implementing examination timetabling systems in universities in Europe, Australasia and America. This model represents the problem that was presented in the 2nd International Timetabling Competition (ITC2007). In presenting this detailed new model, this paper describes the examination timetabling track introduced as part of the competition. In addition to the model, the datasets used in the competition are also based on current real-world instances introduced by EventMAP Limited. It is hoped that the interest generated as part of the competition will lead to the development, investigation and application of a host of novel and exciting techniques to address this important real-world search domain. Moreover, the motivating goal of this paper is to close the currently existing gap between theory and practice in examination timetabling by presenting the research community with a rigorous model which represents the complexity of the real-world situation. In this paper we describe the model and its motivations, followed by a full formal definition

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“…The basic branch and bound method was tested to compare it against PFC. The variable ordering heuristic used in this evaluation is the smallest-domain heuristic [20]. The value ordering heuristic used in this evaluation is to select first the value with minimal inconsistency count [20].…”

Section: Evaluations Of Variants Of Partial Forward Checkingmentioning

confidence: 99%

“…The variable ordering heuristic used in this evaluation is the smallest-domain heuristic [20]. The value ordering heuristic used in this evaluation is to select first the value with minimal inconsistency count [20]. For Reuters-21578 dataset and a list of topics of a user's interest, we compare the performance of these algorithms by varying the user's preference (Fig.…”

Section: Evaluations Of Variants Of Partial Forward Checkingmentioning

confidence: 99%

Intelligent Information Personalization Leveraging Constraint Satisfaction and Association Rule Methods

Zeng

2006

Advances in Artificial Intelligence

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Abstract. Recommender systems, using information personalization methods, provide information that is relevant to a user-model. Current information personalization methods do not take into account whether multiple documents when recommended together present a factually consistent outlook. In the realm of content-based filtering, in this paper, we investigate establishing the factual consistency between the set of documents deemed relevant to a user. We approach information personalization as a constraint satisfaction problem, where we attempt to satisfy two constraints-i.e. user-model constraints to determine the relevance of a document to a user and consistency constraints to establish factual consistency of the overall personalized information. Our information personalization framework involves: (a) an automatic constraint acquisition method, based on association rule mining, to derive consistency constraints from a corpus of documents; and (b) a hybrid of constraint satisfaction and optimization methods to derive an optimal solution comprising both relevant and factually consistent documents. We apply our information personalization framework to filter news items using the Reuters-21578 dataset.

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Untitled

Cited by 22 publications

References 49 publications

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Partial constraint satisfaction approaches for optimal operation of a hydropower system

A new model for automated examination timetabling

Intelligent Information Personalization Leveraging Constraint Satisfaction and Association Rule Methods

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