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, ineq...
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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.
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 st...
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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.
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 l...
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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 logicprogramming 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.
作者:
HIRAISHI, KSchool 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 K...
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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.
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...
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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.
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-base...
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Generalised Assignment Problems (GAP), traditionally solved by Integer programming techniques, are addressed in the light of current constraintprogramming methods. A scheduling application from manufacturing, based o...
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作者:
Trentesaux, DPesin, PTahon, CCNRS
UMR 8530 Lab Automat & Mecan Ind & Humaines Equipe Syst Prod F-59313 Le Mont Houy 09 Valenciennes France
The job-shop scheduling issue is more and more described not only in terms of efficiency (e.g. Makespan), but also in terms of interactivity and practicability. The aim of this paper is to evaluate the ability of two ...
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The job-shop scheduling issue is more and more described not only in terms of efficiency (e.g. Makespan), but also in terms of interactivity and practicability. The aim of this paper is to evaluate the ability of two approaches inherited from artificial intelligence domain to contribute to the solving of this issue: constraintlogic Program ming (CLP) on the one hand, and, on the other hand, Distributed Problem Solving (DPS) inherited from Distributed Artificial Intelligence (DAI). This analysis is achieved through the use of two specific computerised tools: constraint Handling In Prolog (CHIP) as a CLP software and the Distributed Production Scheduling System (DPSS) as a distributed problem solving system. These tools are then evaluated in terms of interactivity, efficiency and practicability. Interactivity is discussed according to qualitative points of view such as the ability to provide efficient decision support, a set of alternative solutions and the possibility to parameterise the algorithms. Efficiency is described in terms of optimality or sub-optimality by the analysis of the Makespan criterion vs. fixed computation time. Practicability is associated to the industrial viability of the methods: ability to cope with real industrial case study or ability to face real industrial contexts. Evaluation is then performed through a multiple criteria analysis. This analysis is achieved given an increasing number of operations to perform. The results highlight the high complementary level of these two approaches, allowing us to provide a framework for a joint integration, which shall be optimised when taking into account the assets of each approach according to the three evaluation criteria. (C) 2001 Elsevier Science Ltd. All rights reserved.
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 ...
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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.
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...
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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.
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