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constraint logic programming with Polynomial constraints over Finite Domains

FUNDAMENTA INFORMATICAE 2018年第1-2期161卷 9-27页

作者： Bergenti, Federico Monica, Stefania Rossi, Gianfranco Univ Parma Dipartimento Sci Matemat Fis & Informat Parco Area Sci 53-A I-43124 Parma Italy

This paper introduces an instantiation of the constraint logic programming scheme called CLP(PolyFD) in which variables take values from finite subsets of the integers and constraints are expressed as equalities, inequalities, and disequalities of polynomials with integer coefficients. Such constraints, which we call polynomial constraints over finite domains, can be treated effectively by means of a specific solver under the assumption that initial approximations of the domains of variables are available. The proposed solver deals with constraints in a canonical form and it uses the modified Bernstein form of polynomials to detect the satisfiability of constraints. The solver is complete and a preliminary assessment of its performance is reported.

关键词： Polynomial constraints over finite domains modified Bernstein form constraint logic programming

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constraint logic programming approach to protein structure prediction -: art. no. 186

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BMC BIOINFORMATICS 2004年第1期5卷 1-12页

作者： Dal Palù, A Dovier, A Fogolari, F Univ Udine Dipartimento Matemat & Informat I-33100 Udine Italy Univ Udine Dipartimento Sci & Tecnol Biomed I-33100 Udine Italy

Background: The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by constraint logic programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results: constraint logic programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, constraint logic programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions: The results obtained on small proteins show that constraint logic programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of constraint logic programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

关键词： Molecular Dynamic Simulation Secondary Structure Element constraint logic programming Secondary Structure Information Core Residue

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constraint logic programming for qualitative and quantitative constraint satisfaction problems

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DECISION SUPPORT SYSTEMS 1996年第1期16卷 67-83页

作者： Lee, HG Lee, RM Yu, G ERASMUS UNIV ROTTERDAM RES INST DECIS & INFORMAT SYST3000 DR ROTTERDAMNETHERLANDS UNIV TEXAS GRAD SCH BUSINESSDEPT MANAGEMENT SCI & INFORMAT SYSTAUSTINTX 78712

AI and OR approaches have complementary strengths: AI in domain-specific knowledge representation and OR in efficient mathematical computation. constraint logic programming (CLP), which combines these complementary strengths of the AI and OR approach, is introduced as a new tool to formalize a special class of constraint satisfaction problems that include both qualitative and quantitative constraints. The CLP approach is contrasted with the Mixed Integer programming (MIP) method from a model-theoretic view. Three relative advantages of CLP over MIP are analyzed: (1) representational economies for domain-specific heuristics, (2) partial solutions, and (3) ease of model revision. A case example of constraint satisfaction problems is implemented by MIP and CLP for comparison of the two approaches. The results exhibit those relative advantages of CLP with computational efficiency comparable to MIP.

关键词： constraint logic programming logic modelling constraint solving

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constraint logic programming framework for integrated decision supports

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DECISION SUPPORT SYSTEMS 1998年第2期22卷 155-170页

作者： Ryu, YU Univ Texas Dept Decis Sci Richardson TX 75083 USA

Decision support systems provide decision-makers with an interactive environment for analyses of information with various models to help solve unstructured problems. constraint logic programming as an improvement of logic programming can be used as a tool for the development of such decision support systems. constraint logic programming is an integrated paradigm of logic modelling and mathematical programming. It has a modelling and analysis capacity for problems containing both qualitative and quantitative constraints;it has well-established declarative and procedural semantics, which reduce the model builder's burden to specify problem solving procedures as a part of a model. In this paper, we demonstrate the use of constraint logic programming as a potential decision support system tool, focusing on the model representation and analysis aspects. (C) 1998 Elsevier Science B.V.

关键词： constraint logic programming decision support systems logic modelling model management

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constraint logic programming for structure-based reasoning about dynamic physical systems

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ARTIFICIAL INTELLIGENCE IN ENGINEERING 1996年第3期10卷 253-264页

作者： ElFattah, Y Information and Computer Science University of California Irvine California 92717 USA

The paper describes a constraint logic programming approach for reasoning about dynamic physical systems based on structure. The approach takes a bond graph model of a system and computes a causal graph representation of its causal structure. Causal graphs can be used for causal explanations and for explaining the effect of modeling abstractions on causal structure. The paper shows how causal graphs can be used to compute a simulation model of a system in the form of a set of differential algebraic equations. The topological properties of the causal graph determine whether a simulation model is regular, i.e. conforming to the criterion of 'real-time representation' or causality. In case the simulation model is not regular, a method is given for identifying all causal problems of a bond graph model.

关键词： constraint logic programming dynamic systems bond graphs causal graphs abstraction simulation

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A constraint logic programming LANGUAGE KEYED CLP AND ITS APPLICATIONS TO DECISION-MAKING PROBLEMS IN OR/MS

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DECISION SUPPORT SYSTEMS 1995年第3期14卷 269-281页

作者： HIRAISHI, K School of Information Science Japan Advanced Institute of Science and Technology Hokuriku 15 Asahi-dai Tatsunokuchi Nomi-gun Ishikawa 923-12 Japan

The aim of this research is to utilize constraint logic programming (CLP) far solving decision making problems in Operations Research/Management Science. In this research, a new constraint logic programming language Keyed CLP is developed. Keyed CLP has some characteristic features for solving problems in OR/MS. Key arguments can be attached to each predicate, where each key represents the functional dependency in the predicate, and is used for improving computational efficiency and readability of programs. In addition, Keyed CLP has built-in predicates for solving linear optimization problems. To illustrate these features, several examples of decisions making problems are solved by Keyed CLP.

关键词： constraint logic programming DECISION MAKING LINEAR programming constraint SOLVING MODELING

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constraint logic programming: Applications and implications

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Artificial Intelligence in Engineering 1992年第3期7卷 175-182页

作者： El Fattah, Yousri Department of Information and Computer Science University of California Irvine CA 92717-3425 United States

The main features of constraint logic programming (CLP) are presented. Examples of using CLP(R) are given to demonstrate the power and limitation of the current implementation. Two application examples from model-based diagnosis and planning are discussed. Some implications of development in CLP on areas of research in artificial intelligence are outlined. © 1992.

关键词： constraint logic programming diagnosis explanation-based learning planning qualitative reasoning

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constraint logic programming and Integer programming approaches and their collaboration in solving an assignment scheduling problem

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constraints 1997年第3期1卷 245-264页

作者： Darby-Dowman, Ken Little, James Mitra, Gautam Zaffalon, Marco Department of Mathematics and Statistics Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Universitá degli Studi di Milano Dip. di Matematica 20129 Milan Via Cicognara 7 Italy

Generalised Assignment Problems (GAP), traditionally solved by Integer programming techniques, are addressed in the light of current constraint programming methods. A scheduling application from manufacturing, based on a modified GAP, is used to examine the performance of each technique under a variety of problem characteristics. Experimental evidence showed that, for a set of assignment problems, constraint logic programming (CLP) performed consistently better than Integer programming (IP). Analysis of the CLP and IP processes identified ways in which the search was effective. The insight gained from the analysis led to an Integer programming approach with significantly improved performance. Finally, the issue of collaboration between the two contrasting approaches is examined with respect to ways in which the solvers can be combined in an effective manner. © 1997 Kluwer Academic Publishers.

关键词： constraint logic programming Generalised assignment problem Integer programming Optimisation

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An extended formalism to constraint logic programming for decision analysis

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KNOWLEDGE-BASED SYSTEMS 2002年第3期15卷 189-202页

作者： Liao, SY Wang, HQ Liao, LJ City Univ Hong Kong Dept Informat Syst Kowloon Hong Kong Peoples R China

While constraint logic programming (CLP) is becoming a favorite tool for decision support systems (DSS), its utility to DSS is limited due to the lack of decision theoretic analysis capability. The combination of CLP with decision theoretic analysis is therefore necessary for more fruitful CLP applications to DSS. In this paper, we propose a framework which embeds decision tree analysis into CLP. The framework provides an integrated representation of decision problems with logic, constraints, probability, and utility. The benefits are threefold. The first is to offer an integrated representation and reasoning mechanism for general knowledge-based decision analysis problems. The second is to provide support to automatic or computer-aided construction of decision trees from the declarative representation of decision problems so that a decision maker can get an intuitive decision scenario from decision trees without manual labor. Last of all, the mechanism of constraint propagation provided by CLP significantly reduces the complexity of decision trees by removing infeasible solutions. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： constraint logic programming decision support systems decision tree analysis decision analysis

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Block structured scheduling using constraint logic programming

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AI COMMUNICATIONS 2020年第1期33卷 41-57页

作者： Badica, Amelia Badica, Costin Ivanovic, Mirjana Univ Craiova Dept Stat & Business Informat Craiova Romania Univ Craiova Dept Comp & Informat Technol Craiova Romania Univ Novi Sad Dept Math & Informat Novi Sad Serbia

We propose a constraint logic programming approach for synthesizing block-structured scheduling processes with ordering constraints. Then we extend the model to allow specification of resource constraints. Our goal is to design optimization algorithms. We combine block structured modeling of business processes with results from project scheduling literature. Differently from standard approaches, here we focus on block structured scheduling processes. Our main achievement is the formulation of an abstract mathematical model of block-structured resource-constrained scheduling processes. We tested the correctness and feasibility of our approach using an experimental prototype based on constraint logic programming developed using ECLiPSe-CLP system.

关键词： Planning & scheduling constraint logic programming optimization

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