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306
The LPSAT Engine & its Application to Resource Planning
, 1999
"... Compilation to boolean satisfiability has become a powerful paradigm for solving AI problems. However, domains... ..."
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Cited by 70 (0 self)
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Compilation to boolean satisfiability has become a powerful paradigm for solving AI problems. However, domains...
Increasing Constraint Propagation by Redundant Modeling: an Experience Report
 CONSTRAINTS
, 1999
"... This paper describes our experience with a simple modeling and programming approach for increasing the amount of constraint propagation in the constraint solving process. The idea, although similar to redundant constraints, is based on the concept of redundant modeling. We introduce the notions of ..."
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Cited by 68 (8 self)
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This paper describes our experience with a simple modeling and programming approach for increasing the amount of constraint propagation in the constraint solving process. The idea, although similar to redundant constraints, is based on the concept of redundant modeling. We introduce the notions of CSP model and model redundancy, and show how mutually redundant models can be combined and connected using channeling constraints. The combined model contains the mutually redundant models as submodels. Channeling constraints allow the submodels to cooperate during constraint solving by propagating constraints freely amongst the submodels. This extra level of pruning and propagation activities becomes the source of execution speedup. We perform two case studies to evaluate the effectiveness and efficiency of our method. The first case study is based on the simple and wellknown nqueens problem, while the second case study applies our method in the design and construction of a reallife ...
Hierarchical Constraint Logic Programming
, 1993
"... A constraint describes a relation to be maintained ..."
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Cited by 67 (3 self)
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A constraint describes a relation to be maintained
On Forward Checking for Nonbinary Constraint Satisfaction
 ARTIFICIAL INTELLIGENCE
, 1999
"... Solving nonbinary constraint satisfaction problems, a crucial challenge for the next years, can be tackled in two different ways: translating the nonbinary problem into an equivalent binary one, or extending binary search algorithms to solve directly the original problem. The latter option rai ..."
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Cited by 66 (4 self)
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Solving nonbinary constraint satisfaction problems, a crucial challenge for the next years, can be tackled in two different ways: translating the nonbinary problem into an equivalent binary one, or extending binary search algorithms to solve directly the original problem. The latter option raises some issues when we want to extend denitions written for the binary case. This paper focuses on the wellknown forward checking algorithm, and shows that it can be generalized to several nonbinary versions, all tting its binary denition. The classical version, proposed by Van Hentenryck, is only one of these generalizations.
Algorithms for hybrid MILP/CP models for a class of optimization problems
 INFORMS Journal on Computing
, 2001
"... The goal of this paper is to develop models and methods that use complementary strengths of Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) techniques to solve problems that are otherwise intractable if solved using either of the two methods. The class of problems considered ..."
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Cited by 66 (11 self)
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The goal of this paper is to develop models and methods that use complementary strengths of Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) techniques to solve problems that are otherwise intractable if solved using either of the two methods. The class of problems considered in this paper have the characteristic that only a subset of the binary variables have nonzero objective function coefficients if modeled as an MILP. This class of problems is formulated as a hybrid MILP/CP model that involves some of the MILP constraints, a reduced set of the CP constraints, and equivalence relations between the MILP and the CP variables. An MILP/CP based decomposition method and an LP/CPbased branchandbound algorithm are proposed to solve these hybrid models. Both these algorithms rely on the same relaxed MILP and feasibility CP problems. An application example is considered in which the leastcost schedule has to be derived for processing a set of orders with release and due dates using a set of dissimilar parallel machines. It is shown that this problem can be modeled as an MILP, a CP, a combined MILPCP OPL model (Van Hentenryck 1999), and a hybrid MILP/CP model. The computational performance of these models for several sets shows that the hybrid MILP/CP model can achieve two to three orders of magnitude reduction in CPU time.
Implementation of Resource Constraints in ILOG SCHEDULE: A Library for the Development of ConstraintBased Scheduling Systems
 Intelligent Systems Engineering
, 1994
"... It has been argued that the use of constraintbased techniques and tools enables the implementation of precise, flexible, efficient and extensible scheduling systems: precise and flexible as the system can take into account any constraint expressible in the constraint language; efficient inasmuch as ..."
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Cited by 63 (8 self)
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It has been argued that the use of constraintbased techniques and tools enables the implementation of precise, flexible, efficient and extensible scheduling systems: precise and flexible as the system can take into account any constraint expressible in the constraint language; efficient inasmuch as highly optimized constraint propagation procedures are now available; extensible as the consideration of a new type of constraint may require (especially in an objectoriented framework) only an extension to the constraint system or, in the worst case, the implementation of additional decisionmaking modules (without needs for modification of the existing code). The following paper presents ILOG SCHEDULE, a C++ library enabling the representation of a wide collection of scheduling constraints in terms of "resources" and "activities." ILOG SCHEDULE is based on SOLVER, the generic software tool for objectoriented constraint programming developed and marketed by ILOG. SOLVER variables and constraints can be accessed from SCHEDULE activities and resources. As a result, the user of SCHEDULE can make use of SOLVER to represent specific constraints, and implement and combine the specific problemsolving strategies that are the most appropriate for the scheduling application under consideration. It is hoped  and expected  that objectoriented constraint programming tools like SCHEDULE will enable the industry to make decisive steps toward the implementation of "state of the art," highly flexible, constraintbased scheduling applications.
Extracting Buildings from Aerial Images using Hierarchical Aggregation in 2D and 3D
, 1998
"... We propose a modelbased approach to automated 3D extraction of buildings from aerial images. We focus on a reconstruction strategy that is not restricted to a small class of buildings. Therefore, we employ a generic modeling approach which relies on the well dened combination of building part mo ..."
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Cited by 61 (4 self)
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We propose a modelbased approach to automated 3D extraction of buildings from aerial images. We focus on a reconstruction strategy that is not restricted to a small class of buildings. Therefore, we employ a generic modeling approach which relies on the well dened combination of building part models. Building parts are classied by their roof type.
Parallel Execution of Prolog Programs: A Survey
"... Since the early days of logic programming, researchers in the field realized the potential for exploitation of parallelism present in the execution of logic programs. Their highlevel nature, the presence of nondeterminism, and their referential transparency, among other characteristics, make logic ..."
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Cited by 61 (24 self)
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Since the early days of logic programming, researchers in the field realized the potential for exploitation of parallelism present in the execution of logic programs. Their highlevel nature, the presence of nondeterminism, and their referential transparency, among other characteristics, make logic programs interesting candidates for obtaining speedups through parallel execution. At the same time, the fact that the typical applications of logic programming frequently involve irregular computations, make heavy use of dynamic data structures with logical variables, and involve search and speculation, makes the techniques used in the corresponding parallelizing compilers and runtime systems potentially interesting even outside the field. The objective of this paper is to provide a comprehensive survey of the issues arising in parallel execution of logic programming languages along with the most relevant approaches explored to date in the field. Focus is mostly given to the challenges emerging from the parallel execution of Prolog programs. The paper describes the major techniques used for shared memory implementation of Orparallelism, Andparallelism, and combinations of the two. We also explore some related issues, such as memory
A Theoretical and Experimental Comparison of Constraint Propagation Techniques for Disjunctive Scheduling
, 1995
"... Disjunctive constraints are widely used to ensure that the time intervals over whichtwo activities require the same resource cannot overlap: if a resource is required bytwo activities A and B, the disjunctive constraint states that either A precedes B or B precedes A. The #propagation " of di ..."
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Cited by 60 (6 self)
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Disjunctive constraints are widely used to ensure that the time intervals over whichtwo activities require the same resource cannot overlap: if a resource is required bytwo activities A and B, the disjunctive constraint states that either A precedes B or B precedes A. The #propagation " of disjunctive constraints consists in determining cases where only one of the two orderings is feasible. It results in updating the timebounds of the two activities. The standard algorithm for propagating disjunctive constraints achieves arcBconsistency.Twotypes of methods that provide more precise timebounds are studied and compared. The #rst type of method consists in determining whether an activity A must, can, or cannot be the #rst or the last to execute among a set of activities that require the same resource. The second consists in comparing the amount of #resource energy" required over a time interval #t 1 t 2 #to the amount of energy that is available over the same interval. The main result of the study is an implementation of the #rst method in Ilog Schedule, a generic tool for constraintbased scheduling which exhibits performance in the same range of e#ciency as speci#c operations research algorithms.
Fuzzy Constraints in JobShop Scheduling
 Journal of Intelligent Manufacturing
, 1995
"... : This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. ..."
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Cited by 53 (9 self)
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: This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. This membership function is obtained by an egalitarist aggregation of local constraintsatisfaction levels. Uncertainty is qualitatively described is terms of possibility distributions. The paper formulates a simple mathematical model of jobshop scheduling under preference and uncertainty, relating it to the formal framework of constraintsatisfaction problems in Artificial Intelligence. A combinatorial search method that solves the problem is outlined, including fuzzy extensions of wellknown lookahead schemes. 1. Introduction There are traditionally three kinds of approaches to jobshop scheduling problems: priority rules, combinatorial optimization and constraint analysis. The first kind ...