Skip to main content
SpringerLink
Log in

Ant Colony Optimization with a Genetic Restart Approach toward Global Optimization

  • Conference paper
Book cover Advances in Computer Science and Engineering (CSICC 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 6))

Included in the following conference series:

Abstract

Ant Colony Optimization (ACO) a nature-inspired metaheuristic algorithm has been successfully applied in the traveling salesman problem (TSP) and a variety of combinatorial problems. In fact, ACO can effectively fit to discrete optimization problems and exploit pre-knowledge of the problems for a faster convergence. We present an improved version of ACO with a kind of Genetic semi-random-restart to solve Multiplicative Square Problem which is an ill-conditioned NP-hard combinatorial problem and demonstrate its ability to escape from local optimal solutions. The results show that our approach appears more efficient in time and cost than the solitary ACO algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dorigo, M.: Optimization, Learning and Natural Algorithms (in Italian). PhD thesis, Dipartimento di Elettronica, Politecnico di Milano, Italy (1992)

    Google Scholar 

  2. Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics – Part B 26, 29–41 (1996)

    Article  Google Scholar 

  3. Gambardella, L.M., Dorigo, M.: Solving symmetric and asymmetric TSPs by ant colonies. In: Proceedings of the 1996 IEEE International Conference on Evolutionary Computation (ICEC 1996), pp. 622–627. IEEE Press, Piscataway (1996)

    Google Scholar 

  4. Lee, Z.J.: A hybrid algorithm applied to travelling salesman problem. In: 2004 IEEE International Conference on Networking, Sensing and Control, vol. 1, pp. 237–242 (2004)

    Google Scholar 

  5. Fu, T.P., Liu, Y.S., Chen, J.H.: Improved Genetic and Ant Colony Optimization Algorithm for Regional Air Defense WTA Problem. In: First International Conference on Innovative Computing, Information and Control (ICICIC 2006), pp. 226–229 (2006)

    Google Scholar 

  6. White, T., Kaegi, S., Oda, T.: Revisiting Elitism in Ant Colony Optimization. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2723, pp. 122–133. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  7. Bullnheimer, B., Hartl, R.F., Strauss, C.: A new rank-based version of the Ant System: A computational study. Central European Journal for Operations Research and Economics 7, 25–38 (1999)

    MathSciNet  MATH  Google Scholar 

  8. Stüzle, T., Hoos, H.: The MAX–MIN Ant System and local search for the traveling salesman problem. In: IEEE International Conference on Evolutionary Computation (ICEC 1997), pp. 309–314. IEEE Press, Piscataway (1997)

    Chapter  Google Scholar 

  9. Kawamura, H., Yamamoto, M., Suzuki, K., Ohuchi, A.: Multiple Ant Colonies Algorithm Based on Colony Level Interactions. IEICE Transactions E83-A, 371–379 (2000)

    Google Scholar 

  10. Dorigo, M., Stüzle, T.: The Ant Colony Optimization Metaheuristic: Algorithms, Application and Advances. Technical Report, IRIDIA-2000-32 (2000)

    Google Scholar 

  11. Dorigo, M., Gambardella, L.M.: Ant Colony System: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1, 53–66 (1997)

    Article  Google Scholar 

  12. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence From Natural to Artificial Systems. Oxford University Press, New York (1999)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Faculty, College of Engineering, University of Tehran, Tehran, Iran

    G. Hossein Hajimirsadeghi, Mahdy Nabaee & Babak N. Araabi

Authors
  1. G. Hossein Hajimirsadeghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mahdy Nabaee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Babak N. Araabi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. IPM School of Computer Science, and Department of Computer Engineering, Sharif Unversity of Technology, Azadi Street, Tehran, Iran

    Hamid Sarbazi-Azad

  2. Department of Electrical and computer Engineering, UC Irvine, California, USA

    Behrooz Parhami

  3. Department of Computer Engineering, Sharif University of Technology,, Azadi Street, Tehran, Iran

    Seyed-Ghassem Miremadi

  4. Department of Computer Engineering, Sharif University of Technology, Azadi Street, Tehran, Iran

    Shaahin Hessabi

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hajimirsadeghi, G.H., Nabaee, M., Araabi, B.N. (2008). Ant Colony Optimization with a Genetic Restart Approach toward Global Optimization. In: Sarbazi-Azad, H., Parhami, B., Miremadi, SG., Hessabi, S. (eds) Advances in Computer Science and Engineering. CSICC 2008. Communications in Computer and Information Science, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89985-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89985-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89984-6

  • Online ISBN: 978-3-540-89985-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation