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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Craenen, B., Eiben, A., van Hemert, J.: Comparing evolutionary algorithms on binary constraint satisfaction problems. IEEE Transactions on Evolutionary Computing 7(5), 424–445 (2003)
Craenen, B.: Solving Constraint Satisfaction Problems with Evolutionary Algorithms. Doctoral dissertation, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (2005)
Glover, F., Laguna, M.: Tabu search. In: Reeves, C. (ed.) Modern Heuristic Techniques for Combinatorial Problems, pp. 70–141. Blackwell Scientific Publishing, Oxford, England (1993)
Costa, D.: An evolutionary tabu search algorithm and the nhl scheduling problem. Orwp 92/11, Ecole Polytechnique Fédérale de Lausanne, Département de Mathématiques, Chaire de Recherche Opérationelle (1992)
Burke, E., Causmaecker, P.D., Berghe, V.: A hybrid tabu search algorithm for the nurse rostering problem. In: Proceedings of the Second Asia-Pasific Conference on Simulated Evolution and Learning. Applications IV, vol. 1, pp. 187–194 (1998)
Greistorfer, P.: Hybrid genetic tabu search for a cyclic scheduling problem. In: Voß, S., Martello, S., Osman, I., Roucairol, C. (eds.) Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, pp. 213–229. Kluwer Academic Publishers, Boston (1998)
Rossi, F., Petrie, C., Dhar, V.: On the equivalence of constrain satisfaction problems. In: Aiello, L. (ed.) Proceedings of the 9th European Conference on Artificial Intelligence (ECAI 1990), Stockholm, Pitman, pp. 550–556 (1990)
MacIntyre, E., Prosser, P., Smith, B., Walsh, T.: Random constraint satisfaction: theory meets practice. In: Maher, M.J., Puget, J.-F. (eds.) CP 1998. LNCS, vol. 1520, Springer, Heidelberg (1998)
Whitley, D.: The genitor algorithm and selection pressure: Why rank-based allocation of reproductive trials is best. In: Schaffer, J. (ed.) Proceedings of the 3rd International Conference on Genetic Algorithms, San Mateo, California, pp. 116–123. Morgan Kaufmann Publisher, Inc., San Francisco (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/11844297_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38990-3
Online ISBN: 978-3-540-38991-0
eBook Packages: Computer ScienceComputer Science (R0)