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Minimizing Conflicts: A Heuristic Repair Method for ConstraintSatisfaction and Scheduling Problems
 J. ARTIFICIAL INTELLIGENCE RESEARCH
, 1993
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueorder ..."
Abstract

Cited by 397 (6 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueordering heuristic, the minconflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. We demonstrate empirically that on the nqueens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. We also describe a scheduling application where the approach has been used successfully. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be most effective.
Minimizing con icts: a heuristic repair methodfor constraint satisfaction andscheduling problems
 Artif. Intell
, 1992
"... Abbreviated Title: \Minimizing Con icts: A Heuristic Repair Method" This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the spa ..."
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Cited by 33 (1 self)
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Abbreviated Title: \Minimizing Con icts: A Heuristic Repair Method" This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by avalueordering heuristic, the mincon icts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of di erent search strategies. We demonstrate empirically that on the nqueens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. We also describe a scheduling application where the approach has been used successfully. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be One of the most promising general approaches for solving combinatorial search problems is to generate an
Analyzing a Heuristic Strategy for ConstraintSatisfaction and Scheduling
 in Intelligent Scheduling
, 1994
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueordering ..."
Abstract

Cited by 26 (3 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueordering heuristic, the minconflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. On the nqueens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. The technique has also been used for scheduling the Hubble Space telescope. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be most effective. 1 Introduction One of the most promising general approaches for solving combinatorial search problems is to generate an initial...
DomainIndependent Local Search For Linear Integer Optimization
, 1998
"... Integer and combinatorial optimization problems constitute a major challenge for algorithmics. They arise when a large number of discrete organizational decisions have to be made, subject to constraints and optimization criteria. This thesis ..."
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Cited by 10 (1 self)
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Integer and combinatorial optimization problems constitute a major challenge for algorithmics. They arise when a large number of discrete organizational decisions have to be made, subject to constraints and optimization criteria. This thesis
Solving partial constraint satisfaction problems using local search and abstraction
, 1992
"... Partial constraint satisfaction problems (PCSPs) were proposed by Freuder and Wallace to address some of the representational di culties with traditional constraint satisfaction techniques. However, the reasoning method of their proposal was limited to traditional backtracking based algorithms. In t ..."
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Cited by 3 (1 self)
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Partial constraint satisfaction problems (PCSPs) were proposed by Freuder and Wallace to address some of the representational di culties with traditional constraint satisfaction techniques. However, the reasoning method of their proposal was limited to traditional backtracking based algorithms. In this paper, we extend the PCSP model by associating it with a local search algorithm, which has found great successes in solving many large scale problems in the past. Furthermore, we extend the combined model to incorporate abstract problem solving, and show that the extended model has not only the advantages of both PCSP and local search, but also a number of new features useful for scheduling applications. We demonstrate the feasibility of our approach by an application to a university course scheduling domain.
Collective Problem Solving through Coordination in a Society of Reactive Agents
, 1994
"... We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), where a problem solution emerges from the evolving computational process of a group of diverse, interacting reactive agents. Problem characteristics are utilized to achieve problem solving by asynchronous and wel ..."
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Cited by 2 (0 self)
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We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), where a problem solution emerges from the evolving computational process of a group of diverse, interacting reactive agents. Problem characteristics are utilized to achieve problem solving by asynchronous and well coordinated local interactions. The coordination mechanisms guide the search space exploration by the society of interacting agents, facilitating rapid convergence to a solution. Our domain of problem solving is constraint satisfaction. We have applied the methodology to job shop scheduling with nonrelaxable time windows, an NPcomplete constraint satisfaction problem. Utility of different types of coordination information in CP&CR was investigated. In addition, experimental results on a benchmark suite of problems show that CP&CR performed considerably well as compared to other centralized search scheduling techniques, in both computational cost and number of problems solved.
Stolving LargeScale Constraint Satisfaction an Scheduling Problems Using a epair Metho
"... This paper describes a simple heuristic method for solving largescale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching though the space of possible repairs. The search is guided by an ordering heuristic, th ..."
Abstract
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This paper describes a simple heuristic method for solving largescale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching though the space of possible repairs. The search is guided by an ordering heuristic, the minconflicts heuristic, that attempts to minimize the number of constraint violations after each step. We demonstrate empirically that the method performs orders of magnitude better than traditional backtracking techniques on certain standard problems. For example, the one million queens problem can be solved rapidly using our approach. We also describe practical scheduling applications where the method has been suc. cessfully applied. A theoretical analysis is presented to explain why the method works so well on certain types of problems and to predict when it is likely to be most effective.