Article ID Journal Published Year Pages File Type
1141541 Discrete Optimization 2011 7 Pages PDF
Abstract

Sat and Max Sat are among the most prominent problems for which local search algorithms have been successfully applied. A fundamental task for such an algorithm is to increase the number of clauses satisfied by a given truth assignment by flipping the truth values of at most kk variables (kk-flip local search). For a total number of nn variables the size of the search space is of order nknk and grows quickly in kk; hence most practical algorithms use 1-flip local search only. In this paper we investigate the worst-case complexity of kk-flip local search, considering kk as a parameter: is it possible to search significantly faster than the trivial nknk bound? In addition to the unbounded case we consider instances with a bounded number of literals per clause and instances where each variable occurs in a bounded number of clauses. We also consider the related problem that asks whether we can satisfy all   clauses by flipping the truth values of at most kk variables.

Related Topics
Physical Sciences and Engineering Mathematics Control and Optimization
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