Heuristics for Improving the Non-oblivious Local Search for MaxSAT

Authors:
G. De Ita;D. E. Pinto;M. Nuño
Affiliations:
-;-;-
Venue:
IBERAMIA '98 Proceedings of the 6th Ibero-American Conference on AI: Progress in Artificial Intelligence
Year:
1998

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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.