A clonal selection algorithm for coloring, hitting set and satisfiability problems

Authors:
Vincenzo Cutello;Giuseppe Nicosia
Affiliations:
Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics and Computer Science, University of Catania, Catania, Italy
Venue:
WIRN'05 Proceedings of the 16th Italian conference on Neural Nets
Year:
2005

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Abstract

In this keynote paper we present an Immune Algorithm based on the Clonal Selection Principle to explore the combinatorial optimization capability. We consider only two immunological entities, antigens and B cells, three parameters, and the cloning, hypermutation and aging immune operators. The experimental results shows how these immune operators couple the clonal expansion dynamics are sufficient to obtain optimal solutions for graph coloring problem, minimum hitting set problem and satisfiability hard instances, and that the IA designed is very competitive with the best evolutionary algorithms.