An ant algorithm for static and dynamic MAX-SAT problems

Authors:
Pedro C. Pinto;Thomas A. Runkler;João M. C. Sousa
Affiliations:
Siemens AG, Corporate Technology, Information and Communications, Munich - Germany and Technical University of Lisbon, Lisbon - Portugal;Siemens AG, Corporate Technology, Information and Communications, Munich - Germany;Technical University of Lisbon, Lisbon - Portugal
Venue:
Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems
Year:
2006

Citing 5
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Reactive search, a history-sensitive heuristic for MAX-SAT

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Abstract

This paper proposes a modified ant colony optimization algorithm, which is applied to the dynamic variant of the maximum satisfiability problem, or MAX-SAT. In the first part of the article we describe the developed algorithm and validate it using previous results of ant optimization applied to normal MAX-SAT problems. In the second part of the article we describe the changes implemented to optimize the dynamic problem and analyze the parameters of the new algorithm. The adapted ant colony optimization accomplishes very well the task of dealing with systematic changes of dynamic MAX-SAT instances derived from static problems.