On selecting a satisfying truth assignment (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
A deterministic (2 - 2/(k+ 1))n algorithm for k-SAT based on local search
Theoretical Computer Science
Deterministic Algorithms for k-SAT Based on Covering Codes and Local Search
ICALP '00 Proceedings of the 27th International Colloquium on Automata, Languages and Programming
A Probabilistic Algorithm for k-SAT and Constraint Satisfaction Problems
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Phase Transitions in Combinatorial Optimization Problems - Basics, Algorithms and Statistical Mechanics
Stochastic Optimization (Scientific Computation)
Stochastic Optimization (Scientific Computation)
Computational Complexity and Statistical Physics (Santa Fe Institute Studies in the Sciences of Complexity Proceedings)
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
A comparative runtime analysis of heuristic algorithms for satisfiability problems
Artificial Intelligence
Comparing two stochastic local search algorithms for constraint satisfaction problems
CSR'10 Proceedings of the 5th international conference on Computer Science: theory and Applications
Choosing probability distributions for stochastic local search and the role of make versus break
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
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We set up a general generic framework for local search algorithms. Then we show in this generic setting how heuristic, problemspecific information can be used to improve the success probability of local search by focussing the search process on specific neighbor states. Our main contribution is a result which states that stochastic local search using restarts has a provable complexity advantage compared to deterministic local search. An important side aspect is the insight that restarting (starting the search process all over, not using any information computed before) is a useful concept which was mostly ignored before.