Abstract
We present a new kind of heuristic guidance as an extension to the Population-based Ant Colony Optimization (P-ACO) implemented in hardware on a Field Programmable Gate Array (FPGA). The heuristic information is obtained by transforming standard heuristic information into small time-scattered heuristic-vectors of favourable ant decisions. This approach is suited for heuristics which allow for an a priori calculation of the heuristics information. Using the proposed method, an ant can build-up a solution in quasi-linear time. Experimental studies measure the performance of the time-scattered heuristic. A comparison with the standard heuristic and candidate lists is also given.
Keywords
- Field Programmable Gate Array
- Hardware Implementation
- Candidate List
- Heuristic Information
- Travel Salesperson Problem
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence. From Natural to Artificial Systems. Oxford University Press, Oxford (1999)
Diessel, O., ElGindy, H., Middendorf, M., Guntsch, M., Scheuermann, B., Schmeck, H., So, K.: Population based ant colony optimization on FPGA. In: IEEE International Conference on Field-Programmable Technology (FPT), pp. 125–132 (December 2002)
Dorigo, M., Di Caro, G.: The ant colony optimization meta-heuristic. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 11–32. McGraw-Hill, New York (1999)
Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5(2), 137–172 (1999)
Dorigo, M., Gambardella, L.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary 1, 53–66 (1997)
Guntsch, M., Middendorf, M.: A population based approach for ACO. In: Cagnoni, S., Gottlieb, J., Hart, E., Middendorf, M., Raidl, G.R. (eds.) EvoIASP 2002, EvoWorkshops 2002, EvoSTIM 2002, EvoCOP 2002, and EvoPlan 2002. LNCS, vol. 2279, pp. 72–81. Springer, Heidelberg (2002)
Johnson, D.S., McGeoch, L.A.: The traveling salesman problem: A case study in local optimization. In: Aarts, E.H.L., Lenstra, J.K. (eds.) Local Search in Combinatorial Optimization, Wiley, Chichester (1995)
Merkle, D., Middendorf, M.: Fast ant colony optimization on runtime reconfigurable processor arrays. Genetic Programming and Evolvable Machines 3(4), 345–361 (2002)
Randall, M., Lewis, A.: A parallel implementation of ant colony optimization. Journal of Parallel and Distributed Computing 62(9), 1421–1432 (2002)
Reinelt, G.: TSPLIB - a traveling salesman problem library. ORSA Journal on Computing 3, 376–384 (1991)
Reinelt, G.: The Traveling Salesman: Computational Solutions for TSP Applications. LNCS, vol. 840. Springer, Heidelberg (1994)
Scheuermann, B., So, K., Guntsch, M., Middendorf, M., Diessel, O., ElGindy, H., Schmeck, H.: FPGA implementation of population-based ant colony optimization. Applied Soft Computing 4, 303–322 (2004)
Shannon, C.E.: A mathematical theory of communication. Bell System Technical Journal 27, 379–423 and s623–656 (1948)
Stützle, T., Dorigo, M.: ACO algorithms for the quadratic assignment problem. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 33–50. McGraw-Hill, New York (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
Scheuermann, B., Guntsch, M., Middendorf, M., Schmeck, H. (2004). Time-Scattered Heuristic for the Hardware Implementation of Population-Based ACO. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2004. Lecture Notes in Computer Science, vol 3172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28646-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-28646-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22672-7
Online ISBN: 978-3-540-28646-2
eBook Packages: Springer Book Archive