A Parallel Hybrid Heuristic for the TSP
In this paper we investigate the design of a coarse-grained parallel implementation of Cga-LK, a hybrid heuristic for the Traveling Salesman Problem (TSP). Cga-LK exploits a compact genetic algorithm in order to generate high-quality tours which are then refined by means of an efficient implementation of the Lin-Kernighan local search heuristic. The results of several experiments conducted on a cluster of workstations with different TSP instances show the efficacy of the parallelism exploitation.
KeywordsParallel algorithms TSP compact genetic algorithm LinKernighan algorithm hybrid GA
Unable to display preview. Download preview PDF.
- 2.J. Grefenstette, R. Gopal, B. Rosimaita, and D. van Gucht. Genetic algorithms for the traveling salesman problem. In Proceedings of the International Conference on Genetics Algorithms and their Applications, pages 160–168, 1985.Google Scholar
- 7.D.S. Johnson and L.A. McGeoch. Local Search in Combinatorial Optimization, chapter The Traveling Salesman Problem: A Case Study in Local Optimization. John Wiley and Sons, New York, 1996.Google Scholar
- 8.D. Applegate, R. Bixby, V. Chvátal, and W. Cook. Finding tours in the tsp. Preliminary chapter of a planned monograph on the TSP, available at URL: http://www.caam.rice.edu/~keck/reports/lk_report.ps, 1999.
- 9.O. Martin and S.W. Otto. Combining simulated annealing with local search heuristic. To appear on Annals of Operation Research.Google Scholar
- 10.P. Merz and B. Freisleben. Genetic local search for the TSP: New results. In Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, pages 159–163, Indianapolis, USA, 1997. IEEE press.Google Scholar
- 11.M. Gorges-Schleuter. Asparagos96 and the travelling salesman problem. In T. Bäck, editor, Proceedings of the Fourth International Conference on Evolutionary Computation, pages 171–174, New York, EEE Press, 1997.Google Scholar
- 12.R. Perego R. Baraglia, J.I. Hidalgo. A hybrid approach for the TSP combining genetics and the Lin-Kerninghan local search. Technical Report CNUCE-B4-2000-007, CNUCE-Institute of the Italian National Research Council, 2000.Google Scholar
- 13.R. Perego R. Baraglia, J.I. Hidalgo. A hybrid approach for the Traveling Salesman Problem. submitted paper.Google Scholar
- 15.D. Thierens and D. Goldberg. Mixing in genetic algorithms. In S. Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, pages 38–45, San Mateo, CA, 1993. Morgan Kaufmann.Google Scholar
- 16.E. Cantu-Paz. A survey of parallel genetic algoritms. Technical Report 97003, University of Illinois at Urbana-Champaign, Genetic Algoritms Lab. (IlliGAL), http://www.gal4.ge.uiuc.edu/illigal.home.html, July 1997.
- 17.M. Tomassini. A survey of genetic algorithms. Technical Report 95/137, Department of Computer Science, Swiss Federal Institute of Technology, Lausanne, Switzerland, July 1995.Google Scholar
- 18.P. Grosso. Computer Simulations of Genetic Adaptation: Parallel Subcomponent Interaction in a Multilocus Model. PhD thesis, University of Michigan, 1985.Google Scholar
- 19.R. Tanese. Parallel genetic algorithms for a hypercube. In Proceedings of the Second International Conference on Genetic Algorithms, pages 177–183. L. Erlbaum Associates, 1987.Google Scholar
- 20.R. Tanese. Distribuited genetic algorithms. In Proceedings of the Third International Conference on Genetic Algorithms, pages 434–440. M. Kaufmann, 1989.Google Scholar
- 22.C. Pettey, M. Lenze, and J. Grefenstette. A parallel genetic algorithm. In Proceedings of the Second International Conference on Genetic Algorithms, pages 155–161. L. Erlbaum Associates, 1987.Google Scholar
- 24.W. Gropp, E. Lusk, and A. Skjellum. Using MPI. Massachusetts Institute of Technology, 1999.Google Scholar
- 25.D.E. Culler and J.P. Singh. Parallel Computer Architecture a Harware/Sotware Approach. Morgan Kaufmann Publishers, Inc., 1999.Google Scholar