Constraint-based local search for Golomb rulers
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This paper presents a constraint-based local search algorithm to find an optimal Golomb ruler of a specified order. While the state-of-the-art search algorithms for Golomb rulers hybridise a range of sophisticated techniques, our algorithm relies on simple tabu meta-heuristics and constraint-driven variable selection heuristics. Given a reasonable time limit, our algorithm effectively finds 16-mark optimal rulers with success rate 60 % and 17-mark rulers with 6 % near-optimality.
Lecture Notes in Computer Science
© 2015 Springer International Publishing AG. This is an electronic version of an article published in Lecture Notes In Computer Science (LNCS), Vol. 9075, pp 322-331, 2015. Lecture Notes In Computer Science (LNCS) is available online at: http://link.springer.com// with the open URL of your article.