Minas Dasygenis
ABSTRACT
Local consistencies stronger than arc consistency have received a lot of attention since the early days of CSP research because of the strong pruning they can achieve. However, they have not been widely adopted by CSP solvers. This is because applying such consistencies can sometimes result in considerably smaller search tree sizes and therefore in important speed-ups, but in other cases the search space reduction may be small, causing severe run time penalties. Taking advantage of recent advances in parallelization, we propose a novel approach for the application of strong local consistencies that can improve their performance by largely preserving the speed-ups they offer in cases where they are successful, and eliminating the run time penalties in cases where they are unsuccessful. This approach is presented in the form of a search algorithm consisting of a master search process, which is a typical CSP solver, and a number of slave processes, which can implement strong local consistency algorithms. The only requirement for the implementation and usage of the proposed algorithm is the availability of a multi-core machine. Preliminary experimental results demonstrate the benefits of the proposed method.
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- Using Parallelization to Efficiently Exploit the Pruning Power of Strong Local Consistencies
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