Abstract
In this paper, some novel improved genetic operations are presented, several combinations of genetic operations are examined and the functions of these operations at different evolutionary stages are analyzed by numerical experiments. The essentiality of the ordering of the gene section, the significance of the evolutionary inversion operation and the importance of the selection model are discussed. Some results provide useful information for the implementation of the genetic operations for solving the traveling salesman problem.
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.
Similar content being viewed by others
References
Choi, I.C., Kim, S.I., Kim, H.S.: A Genetic Algorithm with a Mixed Region Search for the Asymmetric Traveling Salesman Problem. Computers & Operations Research 30(5), 773–786 (2003)
Yoon, H.S., Moon, B.R.: An Empirical Study on the Synergy of Multiple Crossover Operators. IEEE Transactions on Evolutionary Computation 6(2), 212–223 (2002)
Tang, L.X., Liu, J.Y., Rong, A.Y., Yang, Z.H.: Modelling and a Genetic Algorithm Solution for the Slab Stack Shuffling Problem When Implementing Steel Rolling Schedules. International Journal of Production Research 40(7), 1583–1595 (2002)
Fogel, D.B.: Applying Evolutionary Programming to Selected Traveling Salesman Problems. Cybernetics and Systems 24(1), 27–36 (1993)
Chellapilla, K., Fogel, D.B.: Exploring Self-adaptive Methods to Improve the Efficiency of Generating Approximate Solutions to Traveling Salesman Problems using Evolutionary Programming. In: Angeline, P.J., McDonnell, J.R., Reynolds, R.G., Eberhart, R. (eds.) EP 1997. LNCS, vol. 1213, p. 361. Springer, Heidelberg (1997)
Nurnberg, H.T., Beyer, H.G.: Dynamics of Evolution Strategies in the Optimization of Traveling Salesman Problems. In: Angeline, P.J., McDonnell, J.R., Reynolds, R.G., Eberhart, R. (eds.) EP 1997. LNCS, vol. 1213, p. 349. Springer, Heidelberg (1997)
Goldberg, D.E., Lingle, R.: Alleles, Loci and Traveling Salesman Problem. In: Proc. of the Int. Conf. on Genetic Algorithms and Their Applications. Carnegie-Mellon University, pp. 154–159 (1985)
Davis, L.: Job Shop Scheduling with Genetic Algorithms. In: Proc. of the Int. Conf. on Genetic Algorithms and Their Applications. Carnegie-Mellon University, pp. 136–140 (1985)
Chen, G.L., Wang, X.F., Wang, D.S.: Genetic Algorithms and Applications. In: Press of Post and Telecommunications, Bei**g, pp. 137–147 (1996)
Liang, Y.C., Ge, H.W., Zhou, C.G., Lee, H.P., Lin, W.Z., Lim, S.P., Lee, K.H.: Solving Traveling Salesman Problems by Genetic Algorithms. Progress in Natural Science 13(2), 135–141 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ge, H., Liang, Y., Marchese, M., Wang, L. (2006). Mechanism Design and Analysis of Genetic Operations in Solving Traveling Salesman Problems. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_69
Download citation
DOI: https://doi.org/10.1007/11816157_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
eBook Packages: Computer ScienceComputer Science (R0)