Computationally challenging problems arise in the context of many applications, and the
ability to solve these as efficiently as possible is of great practical, and often also economic …

Designing high-performance solvers for computationally hard problems is a difficult and
often time-consuming task. Although such design problems are traditionally solved by the …

This paper presents and analyzes two new efficient local search strategies for the Boolean
Satisfiability (SAT) problem. We start by proposing a local search strategy called …

An interesting strategy called configuration checking (CC) was recently proposed to handle
the cycling problem in local search for Minimum Vertex Cover. A natural question is whether …

Stochastic local search (SLS) algorithms have shown effectiveness on satisfiable instances
of the Boolean satisfiability (SAT) problem. However, their performance is still unsatisfactory …

Stochastic local search (SLS) methods are heuristic-based algorithms that have gained in
popularity for their efficiency and robustness when solving very large and complex problems …

Recently, a number of non-uniform random satisfiability models have been proposed that
are closer to practical satisfiability problems in some characteristics. In contrast to uniform …

Stochastic local search (SLS) methods are well known for their ability to find models of
randomly generated instances of the propositional satisfiability problem (SAT) very …

It is widely acknowledged that stochastic local search (SLS) algorithms can efficiently find
models of satisfiable formulae for the Boolean Satisfiability (SAT) problem. There has been …

It is widely acknowledged that stochastic local search (SLS) algorithms can efficiently find
models for satisfiable instances of the satisfiability (SAT) problem, especially for random k …