This paper summarizes the main existing approaches to propagate resource constraints in constraint-Based scheduling and identifies some of their limitations for using them in an integrated planning and scheduling fram...
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This paper summarizes the main existing approaches to propagate resource constraints in constraint-Based scheduling and identifies some of their limitations for using them in an integrated planning and scheduling framework. We then describe two new algorithms to propagate resource constraints on discrete resources and reservoirs. Unlike most of the classical work in scheduling, our algorithms focus on the precedence relations between activities rather than on their absolute position in time. They are efficient even when the set of activities is not completely defined and when the time window of activities is large. These features explain why our algorithms are particularly suited for integrated planning and scheduling approaches. All our algorithms are illustrated with examples. Encouraging preliminary results are reported on pure scheduling problems as well as some possible extensions of our framework. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper, we describe an aircraft loading problem submitted by the French military agency (DGA) as part of a more general military airlift planning problem. It can be viewed as a kind of bi-dimensional bin-packin...
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In this paper, we describe an aircraft loading problem submitted by the French military agency (DGA) as part of a more general military airlift planning problem. It can be viewed as a kind of bi-dimensional bin-packing problem, with heterogeneous bins and several additional constraints. We introduce two-phase methods for solving this NP-hard problem. The first phase consists in building good initial solutions, thanks to two fast algorithms: a list-based heuristic and a loading pattern generation method. Both algorithms call a constraint-based subroutine, able to determine quickly if the items already loaded can be reshuffled to accommodate a new object. The second phase improves these preliminary solutions using local search techniques. Results obtained on real data sets are presented.
Configuration problems often involve large product catalogs, and the given user requests can be met by many different kinds of parts from this catalog. Hence, configuration problems are often weakly constrained and ha...
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Configuration problems often involve large product catalogs, and the given user requests can be met by many different kinds of parts from this catalog. Hence, configuration problems are often weakly constrained and have many solutions. However, many of those solutions may be discarded by the user as long as more interesting solutions are possible. The user often prefers certain choices to others (e.g., a red color for a car to a blue color) or prefers solutions that minimize or maximize certain criteria such as price and quality. In order to provide satisfactory solutions, a configurator needs to address user preferences and user wishes. Another important problem is to provide high-level features to control different reasoning tasks such as solution search, explanation, consistency checking, and reconfiguration. We address those problems by introducing a preference programming system that provides a new paradigm for expressing user preferences and user wishes and provides search strategies in a declarative and unified way, such that they can be embedded in a constraint and rule language. The preference programming approach is completely open and dynamic. In fact, preferences can be assembled from different sources such as business rules, databases, annotations of the object model, or user input. An advanced topic is to elicit preferences from user interactions, especially from explanations of why a user rejects proposed choices. Our preference programming system has successfully been used in different configuration domains such as loan configuration, service configuration, and other problems.
In this paper,1 we present a semantic theory for the exchange of information in multi-agent systems. We consider the multi-agent programming language agent communication programming language, which integrates the para...
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In this paper,1 we present a semantic theory for the exchange of information in multi-agent systems. We consider the multi-agent programming language agent communication programming language, which integrates the paradigms of concurrent constraint programming and communicating sequential processes (csp). The constraint programming techniques are used to represent and process information, whereas the synchronous communication mechanism from CSP is generalised to enable the exchange of information. The semantics of the language, which is based on a generalisation of traditional failure semantics, is shown to be fully abstract with respect to observing of each terminating computation its final global store of information. (C) 2002 Elsevier Science B.V. All rights reserved.
This paper describes a new method for modeling and solving different scheduling and resource assignment problems that are common in high-level synthesis (HLS) and system-level synthesis. It addresses assignment of res...
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This paper describes a new method for modeling and solving different scheduling and resource assignment problems that are common in high-level synthesis (HLS) and system-level synthesis. It addresses assignment of resources for operations and tasks as well as their static, off-line scheduling. Different heterogeneous constraints are considered for these problems. These constraints can be grouped into two classes: problem-specific constraints and design-oriented constraints. They are uniformly modeled, in our approach, by finite domain (FD) constraints and solved using related constrained programming (CP) techniques. This provides a way to improve quality of final solutions. We have developed in Java a constraint solver engine, JaCoP ( Java constraint programming), to evaluate this approach. This solver and a related framework make it possible to model different resource assignment and scheduling problems, and handle them uniformly. The JaCoP prototype system has been extensively evaluated on a number of HLS and system-level synthesis benchmarks. We have been able to obtain optimal results together with related proofs of optimality for all HLS scheduling benchmarks and for all explored design styles ( except one functional pipeline design). Many system-level benchmarks can also be solved optimally. For large randomly generated task graphs, we have used heuristic search methods and obtained results that are 1 - 3% worse than lower bounds or optimal results. These experiments have proved the feasibility of the presented approach.
A scheduling problem with piecewise linear (PL) optimization extends conventional scheduling by imposing a conjunction of combinatorial PL constraints involving the objective function variables. To solve this problem,...
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A scheduling problem with piecewise linear (PL) optimization extends conventional scheduling by imposing a conjunction of combinatorial PL constraints involving the objective function variables. To solve this problem, this paper presents a hybrid algorithm where constraint programming (CP) search is supported and driven by a (integer) linear programming solver running on a well-controlled subproblem which is dynamically tightened. The paper discusses and compares different ways of decomposing the problem constraints between the CP search and the solver. We show how the subproblem structure and the piecewise linearity are exploited by the search.
Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive f...
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Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive fragment, we now extend the account to all Boolean connectives and propose a new formalism that combines dominance constraints with a feature tree logic. Although the satisfiability problem in the conjunctive fragment is known to be NP-complete, we have previously demonstrated that it can be addressed very effectively by constraint propagation: we developed an encoding that transforms a dominance constraint into a constraint satisfaction problem on finite sets solvable by constraint programming. We present a generalization of this encoding for our more expressive formalism, and prove soundness and completeness. Our main contribution is a treatment of disjunction suitable for constraint propagation. (C) 2002 Published by Elsevier Science B.V.
This paper proposes a novel constraint-based optimization model and a novel search strategy for optimizing the design of a 3G UMTS access network. The model concerns finding a set of sites for locating RNCs, and at th...
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ISBN:
(纸本)0780377818
This paper proposes a novel constraint-based optimization model and a novel search strategy for optimizing the design of a 3G UMTS access network. The model concerns finding a set of sites for locating RNCs, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize a set of objectives. Computational results show that the model and the search strategy are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within 5.77% to 7.48% of the lower bounds.
Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive f...
详细信息
Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive fragment, we now extend the account to all Boolean connectives and propose a new formalism that combines dominance constraints with a feature tree logic. Although the satisfiability problem in the conjunctive fragment is known to be NP-complete, we have previously demonstrated that it can be addressed very effectively by constraint propagation: we developed an encoding that transforms a dominance constraint into a constraint satisfaction problem on finite sets solvable by constraint programming. We present a generalization of this encoding for our more expressive formalism, and prove soundness and completeness. Our main contribution is a treatment of disjunction suitable for constraint propagation. (C) 2002 Published by Elsevier Science B.V.
Maintenance scheduling of generating units is an important problem of power systems operations. Traditional approaches and even more recent ones, provide little flexibility to the modeling process. hi this paper we te...
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ISBN:
(纸本)0889863350
Maintenance scheduling of generating units is an important problem of power systems operations. Traditional approaches and even more recent ones, provide little flexibility to the modeling process. hi this paper we test two search methods, in order to demonstrate that a constraint programming approach can provide the needed modeling flexibility without losing efficiency. One of the methods is complete being the other incomplete, and both are tested with general and specific variable/value selection heuristics. Our test results show that the complete method performs badly in large problem instances and that the specific heuristics perform better than the general ones. Finally a comparison of our results, with those of other approaches, indicates a similar performance.
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