Abstract
We determine special cases where the behaviour of the nonoblivious local search is worse than the behaviour of the classical local search. We propose some modifications to the non-oblivious objective function in order to cover these cases. We present an empirical analysis and comparative results among the analysed algorithms. This empirical analysis shows that non-oblivious local search (that uses the new objective function introduced here) combined with tabu strategy and the use of the complemented value of the last local optimum as a mechanism for re-starting the search, obtains in practice, better solutions than the classical local seach or non-oblivious local seach alone.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Alimonti P., New local search approximation techniques for maximum generalized satisfiability problems, Information Procesing Letters, 57(3), 1996, 151–156.
Battiti R., Protasi M., Reactive search, a history-sensitive heuristic for MAX-SAT, to appear in ACM Journal of Experimental Algorithmics, 1997.
Bellare M., Goldreich O., Sudan M., Free bits, PCP and non-approximability Towards tight results, Proc. 36th An. Symp. on Found. of Comp. Sc.(FOCS), 1995.
Cheeeseman P., Kanesfsky B., Taylor W., Where the really hard problems are, Proceedings of the 12th IJCAI, pp. 163–169. 1991.
De Ita G., Morales G., Heurísticas para mejorar la búsqueda local en el tratamiento del problema de máxima satisfactibilidad, (Iberamia96), 1996.
Feige U., Goemans M., Approximating the value of two prover proof systems with applications to MAX 2SAT and MAX DICUT, Proceeding 32 Symp. on foundations of Computer Science, pp.182–189, 1995.
Gent I.P., Walsh T., An empirical analysis of search in GSAT, Jour. of Artificial Intelligence Research 1, pp.47–59, 1993.
Gu J., Global optimization for Satisfactibility (SAT) Problem, IEEE Transaction on Knowledge and Data Engineering, Vol. 6, No.3, 361–381, June 1994.
Hansen P., B Jaumard, Algorithms for the Maximum Satisfiability Problem, Computing 44, 279–303, 1990.
Johnson D., Approximation algorithms for combinatorial problems, Journal of Computer and System Sciences 9, 256–278, 1974.
Khanna Sanjeev, R. Motwani, M. Sudan and U. Vazirani, On Syntactic versus Computational Views of Approximability, TR95-023 ECCC 1995
Selman B., Kautz H., Cohen B., Local search strategies for Satisfiability testing, Second DIMACS Challenge on Cliques, Coloring, and Satisfiability, Oct. 1993.
Yannakakis M., On the Approximation of Maximum Satisifiability, Journal of Algorithms, Vol. 17, pp. 475–502, 1994.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
De Ita, G., Pinto, D.E., Nuño, M. (1998). Heuristics for Improving the Non-oblivious Local Search for MaxSAT. In: Coelho, H. (eds) Progress in Artificial Intelligence — IBERAMIA 98. IBERAMIA 1998. Lecture Notes in Computer Science(), vol 1484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49795-1_19
Download citation
DOI: https://doi.org/10.1007/3-540-49795-1_19
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64992-2
Online ISBN: 978-3-540-49795-0
eBook Packages: Springer Book Archive