We study analysis of hybrid systems under incomplete knowledge. The class of hybrid systems to be considered is assumed to have the form of a rectangular hybrid automaton such that each constant in invariants and guar...
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We study analysis of hybrid systems under incomplete knowledge. The class of hybrid systems to be considered is assumed to have the form of a rectangular hybrid automaton such that each constant in invariants and guards is given as a parameter. We develop a method based on symbolic computation that computes an approximation of the discrete behaviour of the automaton. We also show an implementation on a constraint logic programming language.
This paper addresses decision-making support for project-driven design and manufacturing processes in small-and medium-size enterprises. The problem considered regards of finding of computationally effective approach ...
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This paper addresses decision-making support for project-driven design and manufacturing processes in small-and medium-size enterprises. The problem considered regards of finding of computationally effective approach aimed at scheduling of a new project subject to constraints imposed by a multi-project environment. In other words, we are looking for an answer whether a given production order specified by its cost and completion time can be accepted in a given manufacturing system specified by available production capability, i.e., the time-constrained resources availability. The problem belongs to a class of multi-mode case project scheduling problems, where the problem of finding a feasible solution is NP-complete. A CLP-based approach is proposed. Illustrative example of its application to a real-life company employing ILOG OPL Studio 3.6 software tool is presented.
Stuckey (1995) has presented a sound and complete procedure for Constructive Negation in constraint logic programming, together with a sufficient condition, called admissible closure, which guarantees an effective imp...
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Stuckey (1995) has presented a sound and complete procedure for Constructive Negation in constraint logic programming, together with a sufficient condition, called admissible closure, which guarantees an effective implementation. In this paper we analyze this condition and relate it to the decidability of the underlying constraint structure. We prove that the admissible closure condition is also necessary to guarantee the existence of an effective implementation of Constructive Negation. (C) 2000 Elsevier Science B.V. All rights reserved.
William Faulkner's non-chronological story telling style has long been a challenge to critics and a puzzle to beginning literature students. "A Rose for Emily,'' one of Faulkner's most frequently ...
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William Faulkner's non-chronological story telling style has long been a challenge to critics and a puzzle to beginning literature students. "A Rose for Emily,'' one of Faulkner's most frequently anthologized stories, exemplifies the complexity of Faulkner's treatment of time. In this paper, we apply a constraint-based problem solving method to an analysis of the chronology of "A Rose for Emily.'' constraint logic programming is a declarative programming language paradigm that solves problems by enforcing constraints among variables. CLP's ability to sort numeric variables that do not yet have definite values makes it possible to sort the events of "A Rose for Emily'' with only fragmented and relative time information. In attempting to sort the events of the story, we find an inconsistency in the temporal references scattered throughout the narrative. After removing this inconsistency, we are able to compare our chronology with earlier ones and discuss the thematic relevance of Faulkner's nonlinear plots.
In this paper, we present two methods to overcome the combinatorial complexity when solving large discrete optimization problems. The basic idea relies on combining mixed integer programming (MIP) and constraintlogic...
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In this paper, we present two methods to overcome the combinatorial complexity when solving large discrete optimization problems. The basic idea relies on combining mixed integer programming (MIP) and constraint logic programming (CLP) to exploit their complementary strengths. These strategies are illustrated in the area of job-shop scheduling and trim-loss problems. Comparisons of the strategies are presented with direct solutions on MIP and CLP problems. (C) 2000 Elsevier Science Ltd. All rights reserved.
The present paper presents a hybrid approach for solving manufacturing scheduling problems, based on the integration between constraint logic programming (CLP) and Genetic Algorithm (GA) approaches. The proposed metho...
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The present paper presents a hybrid approach for solving manufacturing scheduling problems, based on the integration between constraint logic programming (CLP) and Genetic Algorithm (GA) approaches. The proposed methodology is applied to a single line with multiple products and sequence-dependent time. This system model derives from a real case of a company producing sheets for catalytic converters. A sensitivity analysis of the hybrid methodology is carried out to compare the performance of the CLP, GA and integrated CLP-GA approaches. (C) 2003 Elsevier Ltd. All rights reserved.
In this paper, we present two methods to overcome the combinatorial complexity when solving large discrete optimization problems. The basic idea relies on combining mixed integer programming (MIP) and constraintlogic...
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In this paper, we present two methods to overcome the combinatorial complexity when solving large discrete optimization problems. The basic idea relies on combining mixed integer programming (MIP) and constraint logic programming (CLP) to exploit their complementary strengths. These strategies are illustrated in the area of job-shop scheduling and trim-loss problems. Comparisons of the strategies are presented with direct solutions on MIP and CLP problems. (C) 2000 Elsevier Science Ltd. All rights reserved.
To overcome inefficiency in traditional logicprogramming, a declarative programming language COPS is designed based on the notion of concurrent constraintprogramming (CCP). The improvement is achieved by the adoptio...
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To overcome inefficiency in traditional logicprogramming, a declarative programming language COPS is designed based on the notion of concurrent constraintprogramming (CCP). The improvement is achieved by the adoption of constraint-based heuristic strategy and the introduction of deterministic components in the framework of CCP. Syntax specification and an operational semantic description are presented.
We propose a parametric introduction of intensionally defined sets into any CLP(D) language. The result is a language CLP({D}), where constraints over sets of elements of D and over sets of sets of elements, and so on...
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ISBN:
(纸本)3540206426
We propose a parametric introduction of intensionally defined sets into any CLP(D) language. The result is a language CLP({D}), where constraints over sets of elements of D and over sets of sets of elements, and so on, can be expressed. The semantics of CLP({D}) is based on the semantics of logic programs with aggregates and the semantics of CLP over sets. We investigate the problem of constraint resolution in CLP({D}) and propose algorithms for constraints simplification.
This paper presents a, novel partial assignment technique (PAT) that decides which tasks should be assigned to the same resource without explicitly defining assignment of these tasks to a particular resource. Our meth...
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ISBN:
(纸本)1581136889
This paper presents a, novel partial assignment technique (PAT) that decides which tasks should be assigned to the same resource without explicitly defining assignment of these tasks to a particular resource. Our method simplifies the assignment and scheduling steps while imposing a small or no penalty on the final solution quality. This technique is specially suited for problems which have different resources constraints. Our method does not cluster tasks into a new task, as typical clustering techniques do, but specifies which tasks need to be executed on the same processor. Our experiments have shown that PAT, which may produce non-linear groups of tasks, gives better results than linear clustering when multi-resource constraints axe present. Linear clustering was proved to be optimal comparing to all other clusterings for problems with timing constraints only. In this paper, we show that, if used for multi-resource synthesis problem, as it is often used nowadays, linear clustering will produce inferior solutions.
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