Results 1 
5 of
5
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 398 (6 self)
 Add to MetaCart
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.
Spike: Intelligent scheduling of hubble space telescope observations
 Intelligent Scheduling
, 1994
"... ..."
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)
 Add to MetaCart
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...
A Framework for Integrating Artificial Neural Networks and Logic Programming
 INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
, 1995
"... Many reallife problems belong to the class of constraint satisfaction problems (CSP's), which are NPcomplete, and some NPhard, in general. When the problem size grows, it becomes difficult to program solutions and to execute the solution in a timely manner. In this paper, we present a general ..."
Abstract

Cited by 11 (8 self)
 Add to MetaCart
Many reallife problems belong to the class of constraint satisfaction problems (CSP's), which are NPcomplete, and some NPhard, in general. When the problem size grows, it becomes difficult to program solutions and to execute the solution in a timely manner. In this paper, we present a general framework for integrating artificial neural networks and logic programming to provide an efficient and yet easytoprogram environment for solving CSP's. To realize this framework, we propose a novel constraint logic programming language PROCLANN. Operationally, PROCLANN uses the standard goal reduction strategy as frontend to generate constraints and an efficient backend constraintsolver based on artificial neural networks. PROCLANN retains the simple and elegant declarative semantics of constraint logic programming. Its operational semantics is probabilistic in nature. We show that PROCLANN is sound and weakly complete. A novelty of PROCLANN is that while it is a committedchoice l...
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
 Add to MetaCart
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.