A Fast Parallel Genetic Algorithm for Traveling Salesman Problem

  • Chun-Wei Tsai
  • Shih-Pang Tseng
  • Ming-Chao Chiang
  • Chu-Sing Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6083)


In this paper, we present a fast scalable method to reduce the computation time of genetic algorithms for traveling salesman problem, called the Parallel Pattern Reduction Enhanced Genetic Algorithm (PPREGA). The general idea behind the proposed algorithm is twofold: (1) Eliminate the redundant computations of GA on its convergence process by pattern reduction and (2) Minimize the completion time of GA by parallel computing. Our simulation result shows that the proposed algorithm can significantly reduce not only the computation time but also the maximum completion time of GA. Moreover, our simulation result shows further that the loss of the quality of the end result is small.


Genetic Algorithm Computation Time Local Search Travel Salesman Problem Common Gene 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys 35(3), 268–308 (2003)CrossRefGoogle Scholar
  2. 2.
    Martí, R.: Multi-start methods. In: Glover, F.W., Kochenberger, G.A. (eds.) Handbook of Metaheuristics, pp. 355–368. Kluwer Academic Publishers, Boston (1993)Google Scholar
  3. 3.
    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin (1996)zbMATHGoogle Scholar
  4. 4.
    Lee, J.S., Oh, I.S., Moon, B.R.: Hybrid genetic algorithms for feature selection. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(11), 1424–1437 (2004)CrossRefGoogle Scholar
  5. 5.
    Tsai, C.W.: On the Study of Efficient Metaheuristics via Pattern Reduction. PhD thesis, National Sun Yat-sen University, Taiwan, R.O.C (2009)Google Scholar
  6. 6.
    Cantú-Paz, E.: A survey of parallel genetic algorithms. Calculateurs Paralleles, Reseaux et Systems Repartis 10(2), 141–171 (1998)Google Scholar
  7. 7.
    Mühlenbein, H.: Parallel genetic algorithms, population genetics and combinatorial optimization. In: Proceedings of the Third International Conference on Genetic Algorithms, San Francisco, CA, USA, pp. 416–421 (1989)Google Scholar
  8. 8.
    Kohlmorgen, U., Schmeck, H., Haase, K.: Experiences with fine–grained parallel genetic algorithms. In: Annals of Operations Research (1996)Google Scholar
  9. 9.
    Maeda, Y., Ishita, M., Li, Q.: Fuzzy adaptive search method for parallel genetic algorithm with island combination process. International of Journal of Approximate Reasoning 41, 59–73 (2005)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Wang, L., Maciejewski, A.A., Siegel, H.J., Roychowdhury, V.P., Eldridge, B.D.: A study of five parallel approaches to a genetic algorithm for the traveling salesman problem. Intelligent Automation and Soft Computing 11(4), 217–234 (2005)Google Scholar
  11. 11.
    Cantú-Paz, E., Goldberg, D.E.: Efficient parallel genetic algorithms: theory and practice. Computer Methods in Applied Mechanics and Engineering 186(2-4), 221–238 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Cantú-Paz, E.: Efficient and Accurate Parallel Genetic Algorithms. Kluwer Academic Publishers, Norwell (2000)zbMATHGoogle Scholar
  13. 13.
    Tseng, S.P., Tsai, C.W., Chiang, M.C., Yang, C.S.: Fast genetic algorithm based on pattern reduction. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 214–219 (2008)Google Scholar
  14. 14.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Chun-Wei Tsai
    • 1
    • 2
  • Shih-Pang Tseng
    • 1
    • 3
  • Ming-Chao Chiang
    • 1
  • Chu-Sing Yang
    • 2
  1. 1.Computer Science and EngineeringNational Sun Yat-sen UniversityKaohsiungTaiwan
  2. 2.Electrical EngineeringNational Cheng Kung UniversityTainanTaiwan
  3. 3.Computer Science and Information EngineeringTajen UniversityPingtungTaiwan

Personalised recommendations