Abstract
This paper presents Viral System as a new immune-inspired computational intelligence approach to deal with optimization problems. The effectiveness of the approach is tested on the Steiner problem in networks a well known NP-Hard problem providing great quality solutions in the order of the best known approaches or even improving them.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Farmer, J.D., Packard, N., Perelson, A.: The immune system, adaptation and machine learning. Physica D 22, 187–204 (1986)
Cutello, V., Nicosia, G., Pavone, M.: An Immune Algorithm with Stochastic Aging and Kullback Entropy for the Chromatic Number Problem. Journal of Combinatorial Optimization 14(1), 9–33 (2007)
Cutello, V., Nicosia, G., Pavone, M., Timmis, J.: An Immune Algorithm for Protein Structure Prediction on Lattice Models. IEEE Transaction on Evolutionary Computation 11(1), 101–117 (2007)
Cutello, V., Narzisi, G., Nicosia, G., Pavone, M.: Clonal Selection Algorithms: A Comparative Case Study using Effective Mutation Potentials, optIA versus CLONALG. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 13–28. Springer, Heidelberg (2005)
Van Dyke Parunak, H.: Go to the ant: Engineering principles from natural multi-agent systems. Annals of Operations Research 75, 69–101 (1997)
Koch, T., Martin, A.: Solving Steiner tree problems in graphs to optimality. Networks 32(3), 207–232 (1998)
Gendreau, M., Larochelle, J.-F., Sansò, B.: A tabu search heuristic for the Steiner tree problem. Networks 34(2), 162–172 (1999)
Esbensen, H.: Computing near-optimal solutions to the Steiner problem in a graph using genetic algorithm. Networks 26, 173–185 (1995)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cortés, P., García, J.M., Onieva, L., Muñuzuri, J., Guadix, J. (2008). Viral System to Solve Optimization Problems: An Immune-Inspired Computational Intelligence Approach. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-85072-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85071-7
Online ISBN: 978-3-540-85072-4
eBook Packages: Computer ScienceComputer Science (R0)