Abstract
Many different techniques have been developed for fitness landscape analysis. We present a consolidated and uniform implementation inside the heuristic optimization platform HeuristicLab. On top of these analysis methods a new approach to empirical measurement of isotropy is presented that can be used to extend existing methods. Results are shown using the existing implementation within HeuristicLab 3.3.
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
Altenberg, L.: NK Fitness Landscapes. In: The Handbook of Evoluationary Computation, pp. B2.7.2:1–B2.7.2:11. Oxford University Press, Oxford (1997)
Czech, Z.: Statistical measures of a fitness landscape for the vehicle routing problem. In: IEEE International Symposium on Parallel and Distributed Processing, 2008, pp. 1–8 (2008)
Jones, T.: Evolutionary Algorithms, Fitness Landscapes and Search. Ph.D. thesis, University of New Mexico, Albuquerque, New Mexico (1995)
Kauffman, S.A.: The Origins of Order. Oxford University Press, Oxford (1993)
Lawler, E.L., Lenstra, J.K., Kan, A.H.G.R., Shmoys, D.B. (eds.): The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization. Wiley, Chichester (1985)
Pitzer, E., Affenzeller, M.: A Comprehensive Survey on Fitness Landscape Analysis. In: Recent Advances in Intelligent Engineering Systems, pp. 167–196. Springer, Heidelberg (2011)
Reeves, C.R., Rowe, J.E.: Genetic Algorithms. Kluwer, Dordrecht (2003)
Reinelt, G.: Tsplib–a traveling salesman problem library. ORSA Journal on Computing 3(4), 376–384 (1991)
Smith, T., Husbands, P., Layzell, P., O’Shea, M.: Fitness landscapes and evolvability. Evol. Comput. 10(1), 1–34 (2002)
Stadler, P.F., Grüner, W.: Anisotropy in fitness landscapes. J. Theor. Biol. 165(3), 373–388 (1993)
Stadler, P., Wagner, G.: The algebraic theory of recombination spaces. Evol.Comp. 5, 241–275 (1998)
Vassilev, V.K., Fogarty, T.C., Miller, J.F.: Information characteristics and the structure of landscapes. Evol. Comput. 8(1), 31–60 (2000)
Wagner, S.: Heuristic Optimization Software Systems - Modeling of Heuristic Optimization Algorithms in the HeuristicLab Software Environment. Ph.D. thesis, Johannes Kepler University, Linz, Austria (2009)
Wagner, S., Kronberger, G., Beham, A., Winkler, S., Affenzeller, M.: Modeling of heuristic optimization algorithms. In: Proceedings of the 20th European Modeling and Simulation Symposium, pp. 106–111. DIPTEM University of Genova (2008)
Weinberger, E.: Correlated and uncorrelated fitness landscapes and how to tell the difference. Biological Cybernetics 63(5), 325–336 (1990)
Wright, S.: The roles of mutation, inbreeding, crossbreeding and selection in evolution. In: Proceedings of the Sixth International Congress of Genetics, vol. 1, pp. 356–366 (1932)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pitzer, E., Affenzeller, M., Beham, A., Wagner, S. (2012). Comprehensive and Automatic Fitness Landscape Analysis Using HeuristicLab. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2011. EUROCAST 2011. Lecture Notes in Computer Science, vol 6927. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27549-4_54
Download citation
DOI: https://doi.org/10.1007/978-3-642-27549-4_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27548-7
Online ISBN: 978-3-642-27549-4
eBook Packages: Computer ScienceComputer Science (R0)