Abstract
In this paper, a new and systematic approach for the integration of fuzzy-based methods and biological computation, named as an evolutionary and biological method, is proposed for searching cliques in a fuzzy graph. When dealing with a number of nodes in a graph, the most intractable problem is often detecting the maximum clique, which is automatically obtained from finding a solution to the arranged cliques in descending order. The evolutionary and biological method is proposed to identify all the cliques and to arrange them in a fuzzy graph, and then to structure all the nodes in the graph, based on the searched cliques, in different hierarchical levels. This challenging approach, involving the integration of two techniques, provides a new and better method for solving clique problems.
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
Bomze, I.M., Pelillo, M., Stix, V.: Approximating the maximum weight clique using replicator dynamics. IEEE Transactions on Neural Networks 11, 1228–1241 (2000)
Watada, J., Jeng, D.J.-F., Kim, I.: Application of DNA computing to group control of elevators. In: Iasi, A.I. (ed.) 2005 Anniversary Symposium on the Romanian Society for Fuzzy Systems, A.I., Iasi, Romania, pp. 9–19 (2005)
Watada, J.: DNA computing and its application. In: Proceedings of the 8th International Conference on Intelligent Systems Design and Applications, Keynote Speech, Kaohsiung, Taiwan (2008)
Jeng, D.J.-F., Kim, I., Watada, J.: Bio-inspired evolutionary method for cable trench problem. International Journal of Innovative Computing, Information and Control 3(1), 111–118 (2006)
Rosenfeld, A.: Fuzzy graphs, fuzzy sets and their applications. In: Zadeh, L.A., Fu, K.S., Shimura, M. (eds.), pp. 77–95. Academic Press, New York (1975)
van Noort, D., Landweber, L.F.: Towards a re-programmable DNA computer. In: Chen, J., Reif, J.H. (eds.) DNA 2003. LNCS, vol. 2943, pp. 190–196. Springer, Heidelberg (2004)
Rose, J.A., Hagiya, M., Deaton, R.J., Suyama, A.: A DNA-based in vitro genetic program. Journal of Biological Physics 28, 493–498 (2002)
Sakamoto, K., Kiga, D., Komiya, K., Gouzu, H., Yokoyama, S., Ikeda, S., Sugiyama, H., Hagiya, M.: State transitions by molecules. Biosystems 52, 81–91 (1999)
Adleman, L.: Molecular computation of solutions to combinatorial problems. Science 266(11), 1021–1024 (1994)
Ouyang, Q., Kaplan, P.D., Liu, S., Libacher, A.: DNA solution of the maximal clique problem. Science 278, 446–449 (1997)
Nair, P.S., Cheng, S.-C.: Cliques and fuzzy cliques in fuzzy graphs. In: IFSA World Congress and 20th NAFIPS International Conference, pp. 2277–2280 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, I., Watada, J. (2009). Searching Cliques in a Fuzzy Graph Based on an Evolutionary and Biological Method. In: Velásquez, J.D., RÃos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-04592-9_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04591-2
Online ISBN: 978-3-642-04592-9
eBook Packages: Computer ScienceComputer Science (R0)