Abstract
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.
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Polash, M.M.A., Newton, M.A.H., Sattar, A. (2015). Constraint-Based Local Search for Golomb Rulers. In: Michel, L. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2015. Lecture Notes in Computer Science(), vol 9075. Springer, Cham. https://doi.org/10.1007/978-3-319-18008-3_22
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DOI: https://doi.org/10.1007/978-3-319-18008-3_22
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