Abstract
Heuristic search techniques can often benefit from record keeping and saving of intermediate results, thereby improving performance through exploitation of time / space tradeoffs. Iterative hill climbing (ITHC) is one of these heuristics. This paper demonstrates that record keeping in the ITHC domain can significantly speed up the ITHC. The record keeping method is similar to the mechanism of a cache. The new approach is implemented and tested in the traveling salesperson search space. The research compares a traditional random restart (RR) procedure to a new greedy enumeration (GE) method. GE produces Hamiltonian-cycles that are about 10% shorter than the RR. Moreover, the cached RR achieves a speedup of 3x with a relatively small number of cities and only 20% with a medium number of cities (~17). The cached GE shows a highly significant speedup of 4x over traditional methods even with a relatively large number of cities (>80).
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
Garey, M.R., Johnson, D.S.: Computers and intractability: A guide to the theory of NP-completeness. W.H. Freeman, New York (1979)
Pearl, J.: Heuristics: Intelligent search strategies for computer problem solving. Addison-Wesley, Reading (1984)
Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220, 671–680 (1983)
Vose, M.D.: The simple genetic algorithm: Foundations and theory. MIT Press, Cambridge (1999)
Russell, S.J., Norvig, P.: Artificial intelligence: A modern approach, 2nd edn. Prentice-Hall, Englewood Cliffs (1995)
Xi, B., Liu, Z., Raghavachari, M., Xia, C., Zhang, L.: A smart hill-climbing algorithm for application server configuration. In: Proceedings of the 13th international conference on world wide web, pp. 287–296 (2004)
Hertel, P., Pitassi, T.: An exponential time/space speedup for resolution. Electronic Colloquium on Computational Complexity 46, 1–25 (2007)
Allen, D., Darwiche, A.: Optimal time-space tradeoff in probabilistic inference. In: Proceedings of the 21st international joint conference on artificial intelligence, pp. 969–975 (2003)
Ganapathy, G., Ramachandran, V., Warnow, T.: Better hill-climbing searches for parsimony. Algorithms in Bioinformatics, 245–258 (2004)
Johnson, D.S., McGeoch, L.A.: The traveling salesman problem: A case study in local optimization. Local search in combinatorial optimization, 215–310 (1997)
Applegate, D.L., Bixby, R.E., Vasek, C., Cook, W.J.: The traveling salesman problem: A computational study. Princeton University Press, Princeton (2007)
Zilberstein, S.: Using anytime algorithms in intelligent systems. AI Magazine 17(3), 73–83 (1996)
McMahan, H., Gordon, G.: A fast bundle-based anytime algorithm for poker and other convex games. In: Proceedings of the 11th international conference on artificial intelligence and statistics, pp. 323–330 (2007)
Ramos, T., Cozman, G.: Anytime anyspace probabilistic inference. International Journal of Approximate Reasoning 38(1), 53–80 (2005)
Stone, H.S.: High-performance computer architecture. Prentice-Hall, Englewood Cliffs (1993)
Vanichpun, S., Malkowski, A.M.: Comparing strength of locality of reference – popularity, majorization, and some folk theorems. In: 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, pp. 838–839 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Karhi, D., Tamir, D.E. (2009). Caching in the TSP Search Space. In: Chien, BC., Hong, TP., Chen, SM., Ali, M. (eds) Next-Generation Applied Intelligence. IEA/AIE 2009. Lecture Notes in Computer Science(), vol 5579. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02568-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-02568-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02567-9
Online ISBN: 978-3-642-02568-6
eBook Packages: Computer ScienceComputer Science (R0)