Abstract
The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameters of the algorithm was performed to optimise the performance of the algorithm on a commonly used test-set. The performance of the STLEA was then compared to the best known evolutionary algorithm and benchmark deterministic and non-deterministic algorithms. The comparison shows that the STLEA improves on the performance of the best known evolutionary algorithm but can not achieve the efficiency of the deterministic algorithms.
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Craenen, B.G.W., Paechter, B. (2006). A Tabu Search Evolutionary Algorithm for Solving Constraint Satisfaction Problems. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_16
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DOI: https://doi.org/10.1007/11844297_16
Publisher Name: Springer, Berlin, Heidelberg
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