Abstract
Nature-inspired metaheuristics are effective strategies for solving optimization problems. However, when trying to solve an instance of this kind of problems it is hard to know which algorithm should be used (algorithm-instance problem). Hybrid systems provide flexible tools that can help to cope with this problem. Therefore a hybrid system based on the intelligent combination of different natureinspired strategies will give more robustness and will allow to find higher quality solutions for different instance types.
In this paper we show the construction of a nature-inspired hybrid system, and analyse a study case.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cadenas J.M, Garrido M.C, Hernández L.D, Muñoz E (2006) Towards a definition of a Data Mining process based on Fuzzy Sets for Cooperative Metaheuristic systems. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU2006, 2828–2835, Paris
Cadenas J.M, Garrido M.C, Liern V, Muñoz E, Serrano E (2007) Un prototipo del coordinador de un Sistema Metaheurstico Cooperativo para el Problema de la Mochila. V congreso espaol sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados, MAEB07, 811–818, Tenerife
Cohoon J, Martin W, Richards D (1991) A multi-population genetic algorithm for solving the k-partition problem on hyper-cubes. In: Richar K. Velw, Lashon B. Booker (eds) Fourth International Conference on Genetic Algorithms, San Mateo. CA: MOrgan Kaufmann Publishers
Crainic T.G, Gendreau M, Hansen P, Mladenovic N (2004) Cooperative parallel variable neighborhood search for the p-median. Journal of Heuristics 10:293–314
Guo H (2003) A Bayesian Approach for Automatic Algorithm Selection. IJCAI03 Workshop on AI and Autonomic Computing, 1–5, Mexico
Janikow C.Z (1998) Fuzzy decision trees: issues and methods. IEEE Transaction System, Man, and Cybernetics, Part B. 28(1):1–14
Le Bouthillier A, Crainic T.G (2003) A cooperative parallel meta-heuristic for the vehicle routing problem with time windows. Computers and Operations Research 32(7):1685–1708
Moreno-Velo F.J, Baturone I, Snchez-Solano S, Barriga A (2001) XFUZZY 3.0: A Development Environment for Fuzzy Systems. International Conference in Fuzzy Logic and Technology, 93–96, Leicester
Pelta D, Cruz C, Sancho-Royo A, Verdegay J.L (2006) Using memory and fuzzy rules in a cooperative multi-thread strategy for optimization. Information Sciences 176(13):1849–1868
Rice J.R (1976) The algorithm selection problem. Advances in Computers 15:65–118
University of Waikato. Weka, Data Mining with Open Source Machine Learning Software in Java. URL: http://www.cs.waikato.ac.nz/ml/weka/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Cadenas, J.M., Garrido, M.C., Muñoz, E. (2008). A Hybrid System of Nature Inspired Metaheuristics. In: Krasnogor, N., Nicosia, G., Pavone, M., Pelta, D. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Studies in Computational Intelligence, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78987-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-78987-1_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78986-4
Online ISBN: 978-3-540-78987-1
eBook Packages: EngineeringEngineering (R0)