Critical Parallelization of Local Search for MAX-SAT

In this work we investigate the effects of the parallelization of a local search algorithm for MAX-SAT. The variables of the problem are divided in subsets and local search is applied to each of them in parallel, supposing that variables belonging to other subsets remain unchanged. We show empirical evidence for the existence of a critical level of parallelism which leads to the best performance. This result allows to improve local search and adds new elements to the investigation of criticality and parallelism in combinatorial optimization problems.

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