This paper describes a simple heuristic approach to solving large-scale 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 value-ordering heuristic, the min-conflicts 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 n-queens 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...
This paper presents a general learning method for dynamically selecting between repair heuristics in...
Abstract. Many real-world constraint satisfaction problems (CSPs) can be over-constrained or too lar...
Abstract This paper describes DTS, a decisiontheoretic scheduler designed to employ stateof-the-art ...
This paper describes a simple heuristic method for solving large-scale constraint satisfaction and s...
The work described in this paper was inspired by a surprisingly effective neural network developed f...
Many practical problems can be formulated as constraint satisfaction problems (CSPs), where the goal...
In this paper, we introduce a new solving algorithm for Constraint Satisfaction Problems (CSP). It p...
AbstractPractical constraint satisfaction problems (CSPs) such as design of integrated circuits or s...
[[abstract]]Search algorithms for solving CSP (Constraint Satisfaction Problems) usually fall into o...
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operation...
Algorithms for solving constraint satisfcation problems (CSP) have been successfully applied to seve...
There has been substantial recent interest in two new families of search techniques. One family cons...
International audienceThe variable ordering heuristic is an important module in algorithms dedicated...
AbstractA constraint satisfaction problem (CSP) is said to be overconstrained if it does not have a ...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
This paper presents a general learning method for dynamically selecting between repair heuristics in...
Abstract. Many real-world constraint satisfaction problems (CSPs) can be over-constrained or too lar...
Abstract This paper describes DTS, a decisiontheoretic scheduler designed to employ stateof-the-art ...
This paper describes a simple heuristic method for solving large-scale constraint satisfaction and s...
The work described in this paper was inspired by a surprisingly effective neural network developed f...
Many practical problems can be formulated as constraint satisfaction problems (CSPs), where the goal...
In this paper, we introduce a new solving algorithm for Constraint Satisfaction Problems (CSP). It p...
AbstractPractical constraint satisfaction problems (CSPs) such as design of integrated circuits or s...
[[abstract]]Search algorithms for solving CSP (Constraint Satisfaction Problems) usually fall into o...
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operation...
Algorithms for solving constraint satisfcation problems (CSP) have been successfully applied to seve...
There has been substantial recent interest in two new families of search techniques. One family cons...
International audienceThe variable ordering heuristic is an important module in algorithms dedicated...
AbstractA constraint satisfaction problem (CSP) is said to be overconstrained if it does not have a ...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
This paper presents a general learning method for dynamically selecting between repair heuristics in...
Abstract. Many real-world constraint satisfaction problems (CSPs) can be over-constrained or too lar...
Abstract This paper describes DTS, a decisiontheoretic scheduler designed to employ stateof-the-art ...