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In recent years, with the massive use of Golomb rulers in various fields of engineering, new optimal rulers have become an important subject of search. Many different approaches have been proposed to tackle the Golomb ruler problem such as exact methods, constraint programming, local searches and evolutionary algorithms. This paper describes an hybrid evolutionary algorithm to find optimal or near-optimal Golomb rulers. The obtained results are promising: we are capable of solving large rulers for up to 23 marks.