In recent years, there has been much research on local search techniques for solving constraint satisfaction problems, including Boolean satisfiability problems. Some of the most successful procedures combine a form of random walk with a greedy bias. These procedures are quite e#ective in a number of problem domains, for example, constraint-based planning and scheduling, graph coloring, and hard random problem instances. However, i
Recently there has been a great amount of interest in Random Constraint Satisfaction Problems, both ...
For a large number of random constraint satisfaction problems, such as random $k$-SAT and random gra...
. The goal of this paper is twofold. First, we introduce a class of local search procedures for solv...
Constraint satisfaction plays an important role in theoretical and applied computer science. Constr...
Constraint satisfaction problems (CSPs) are at the core of many tasks with di-rect practical relevan...
Stochastic local search is one of the most successful methods for model finding in propositional sat...
Random K-satisfiability (K-SAT) is a model system for studying typical-case complexity of combinator...
Schöning [25] presents a simple yet elegant randomized algorithm for (d, k)-CSP problems with a run...
We present ULSA, a novel stochastic local search algorithm for random binary constraint satisfaction...
For a number of random constraint satisfaction problems, such as random k-SAT and random graph/hyper...
This paper introduces a genetic local search algorithm for bi-nary constraint satisfaction problems....
The use of randomness in local search is a widespread technique applied to improve algorithm perform...
Much excitement has been generated by the success of stochastic local search procedures at finding s...
For a large number of random Boolean constraint satisfaction problems, such as random $k$-SAT, we st...
Optimization is fundamental in many areas of science, from computer science and information theory t...
Recently there has been a great amount of interest in Random Constraint Satisfaction Problems, both ...
For a large number of random constraint satisfaction problems, such as random $k$-SAT and random gra...
. The goal of this paper is twofold. First, we introduce a class of local search procedures for solv...
Constraint satisfaction plays an important role in theoretical and applied computer science. Constr...
Constraint satisfaction problems (CSPs) are at the core of many tasks with di-rect practical relevan...
Stochastic local search is one of the most successful methods for model finding in propositional sat...
Random K-satisfiability (K-SAT) is a model system for studying typical-case complexity of combinator...
Schöning [25] presents a simple yet elegant randomized algorithm for (d, k)-CSP problems with a run...
We present ULSA, a novel stochastic local search algorithm for random binary constraint satisfaction...
For a number of random constraint satisfaction problems, such as random k-SAT and random graph/hyper...
This paper introduces a genetic local search algorithm for bi-nary constraint satisfaction problems....
The use of randomness in local search is a widespread technique applied to improve algorithm perform...
Much excitement has been generated by the success of stochastic local search procedures at finding s...
For a large number of random Boolean constraint satisfaction problems, such as random $k$-SAT, we st...
Optimization is fundamental in many areas of science, from computer science and information theory t...
Recently there has been a great amount of interest in Random Constraint Satisfaction Problems, both ...
For a large number of random constraint satisfaction problems, such as random $k$-SAT and random gra...
. The goal of this paper is twofold. First, we introduce a class of local search procedures for solv...