Abstract
Previous work investigating the performance of genetic algorithms (GAs) has attempted to develop a set of fitness landscapes, called “Royal Roads” functions, which should be ideally suited for search with GAs. Surprisingly, many studies have shown that genetic algorithms actually perform worse than random mutation hill-climbing on these landscapes, and several different explanations have been offered to account for these observations. Using a detailed stochastic model of genetic search on R1, we attempt to determine a lower bound for the required number of function evaluations, and then use it to evaluate the performance of an actual genetic algorithm on R1.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Baluja, S., Caruana, R.: ‘Removing the Genetics from the Standard Genetic Algorithm. In: Prieditis, A., Russell, S. (eds.) The Proceedings of the 12th Annual Conference on Machine Learning, pp. 38–46. Morgan Kauffman, San Francisco (1995)
Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science 220, 671–680 (1983)
Koehler, G., Bhattacharyya, S., Vose, M.D.: General Cardinality Genetic Algorithms. Evolutionary Computation 5(4), 439–459 (1997)
Mitchell, M., Holland, J.H., Forrest, S.: When Will a Genetic Algorithm Outperform Hill Climbing. In: Cowan, J.D., Tesauro, G., Alspector, J. (eds.) Advances In Neural Information Processing Systems 6, Morgan Kaufmann, San Mateo (1994)
Mitchell, M.: Introduction To Genetic Algorithms. MIT Press, Cambridge (1998)
Suzuki, H., Sawai, H.: Crossover Accelerates Evolution In GA with a Royal Road Function. In: 2001 Genetic and Evolutionary Computation Conference Late Breaking papers, pp. 401–412 (2001)
van Nimwegen, E., Crutchfield, J.P., Mitchell, M.: Statistical Dynamics of the Royal Road Genetic Algorithm. Theoretical Computer Science 229, 41–102 (1999)
Vose, M.D.: Modeling Alternate Selection Schemes For Genetic Algorithms. In: Koppel, M., Shamir, E. (eds.) Proceedings of BISFAI 1995, pp. 166–178. AAAI Press, Israel (1995)
Vose, M.D.: Random Heuristic Search. Theoretical Computer Science 229, 103–142 (1999)
Vose, M.D.: The Simple Genetic Algorithm: Foundations and Theory. MIT Press, Cambridge, MA (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Howard, B., Sheppard, J. (2004). The Royal Road Not Taken: A Re-examination of the Reasons for GA Failure on R1. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_117
Download citation
DOI: https://doi.org/10.1007/978-3-540-24854-5_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22344-3
Online ISBN: 978-3-540-24854-5
eBook Packages: Springer Book Archive