Abstract
Self-adaptation is becoming a standard method for optimizing mutational parameters within evolutionary programming. The majority of these efforts have been applied to continuous optimization problems. This paper offers a preliminary investigation into the use of self-adaptation for discrete optimization using the traveling salesman problem. Two self-adaptive approaches are analyzed. The results indicate that the use of self-adaptation can yield statistically significantly improved solutions over the failure to use any self-adaptation at all. This improvement comes at the expense of greater computational effort.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
P. Ablay (1987) “Optimieren mit der Evolutionsstrategie,” Spektrum der Wissenschaft, July, pp. 104–115.
P.J. Angeline (1996) “The Effects of Noise on Self-Adaptive Evolutionary Optimization,” Evolutionary Programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming, L.J. Fogel, P.J. Angeline, and T. Bäck (eds.), MIT Press, Cambridge, MA, pp. 433–439.
P.J. Angeline, D.B. Fogel, and L.J. Fogel (1996) “A Comparison of Self-Adaptation Methods for Finite State machines in Dynamic Environments,” Evolutionary Programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming, L.J. Fogel, P.J. Angeline, and T. Bäck (eds.), MIT Press, Cambridge, MA, pp. 441–449.
T. Bäck (1996) Evolutionary Algorithms in Theory and Practice, Oxford, NY.
E. Bonomi and J.-L. Lutton (1984) “The N-City Traveling Salesman Problem: Statistical Mechanics and the Metropolis Algorithm,” S1AM Review, Vol. 26:4, pp. 551–569.
L. Davis (ed.) (1991) Handbook of Genetic Algorithms, Van Nostrand Reinhold, NY.
D.B. Fogel (1988) “An Evolutionary Approach to the Traveling Salesman Problem,” Biological Cybernetics, Vol. 60:2, pp. 139–144.
D.B. Fogel (1993a) “Applying Evolutionary Programming to Selected Traveling Salesman Problems,” Cybernetics and Systems, Vol. 24, pp. 27–36.
D.B. Fogel (1993b) “Empirical Estimation of the Computation Required to Discover Approximate Solutions to the Traveling Salesman Problem Using Evolutionary Programming,” Proceedings of the Second Annual Conference on Evolutionary Programming, D.B. Fogel and W. Atmar (eds.), Evolutionary Programming Society, La Jolla, CA, pp. 56–61.
D.B. Fogel (1995) Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, NY.
D.B. Fogel, L.J. Fogel, and J.W. Atmar (1991) “Meta-Evolutionary Programming,” Proceedings of the 25th Asilomar Conference on Signals, Systems, and Computers, R.R. Chen (ed.), Maple Press, San Jose, CA, pp. 540–545.
D.B. Fogel and A. Ghozeil (1996) “Using Fitness Distributions to Design More Efficient Evolutionary Computations,” Proceedings of the 1996 IEEE Conference on Evolutionary Computation, Nagoya, Japan, IEEE Press, pp. 11–19.
D.E. Goldberg and R. Lingle (1985) “Alleles, Loci, and the Traveling Salesman Problem,” Proceedings of an International Conference on Genetic Algorithms and Their Applications, J.J. Grefenstette (ed.), Lawrence Erlbaum, Hillsdale, NJ, pp. 154–159.
J.J. Grefenstette, R. Gopal, B. Rosmaita, and D. Van Gucht (1985) “Genetic Algorithms for the Traveling Salesman Problem,” Proceedings of an International Conference on Genetic Algorithms and Their Applications, J.J. Grefenstette (ed.), Lawrence Erlbaum, Hillsdale, NJ, pp. 160–168.
H.R. Lewis and C.H. Papadimitriou (1981) Elements of the Theory of Computation, Prentice-Hall, Englewood Cliffs, NJ.
I. Rechenberg (1973) Evolutionsstrategie: Optimierung Technischer Systeme nach Prinzipien der Biologischen Evolution, Fromman-Holzboog Verlag, Stuttgart, Germany.
N. Saravanan, D.B. Fogel, and K.M. Nelson (1995) “A Comparison of Methods for Self-Adaptation in Evolutionary Algorithms,” BioSystems, Vol. 36, pp. 157–166.
H.-P. Schwefel (1981) Numerical Optimization of Computer Models, Chichester, U.K.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chellapilla, K., Fogel, D.B. (1997). Exploring self-adaptive methods to improve the efficiency of generating approximate solutions to traveling salesman problems using evolutionary programming. In: Angeline, P.J., Reynolds, R.G., McDonnell, J.R., Eberhart, R. (eds) Evolutionary Programming VI. EP 1997. Lecture Notes in Computer Science, vol 1213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014825
Download citation
DOI: https://doi.org/10.1007/BFb0014825
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-62788-3
Online ISBN: 978-3-540-68518-0
eBook Packages: Springer Book Archive