Skip to main content
SpringerLink
Log in

Variable Neighborhood Search with Permutation Distance for QAP

  • Conference paper
Book cover Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3684))

Abstract

QAP is a famous \(\mathcal{NP}-\)Hard [1] combinatorial optimization problem. Many theoretical and real-life problems could be modeled as it. VNS is a recent metaheuristic and shows good performance in dealing with QAP [2]. In this paper, a new concept distance called permutation distance is proposed and exploited in detail. With permutation distance ready, we combine the hamming distance with it and propose a group of new neighborhood structures in QAP for VNS. Numerical tests running on the standard benchmark library QAPLIB [3] show that this approach would dramatically improve the performance of VNS for QAP. It surpasses some famous metaheuristics and belongs to the most efficient metaheuristics for QAP.

Partially supported by a NKBRPC (2004CB318000) and NSFC (60373002, 60496322).

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Sahni, S., Gonzalez, T.: P-complete approximation problems. Journal of the ACM 23, 555–565 (1976)

    Article  MATH  MathSciNet  Google Scholar 

  2. Taillard, E., Gambardella, L.M.: Adaptive memories for the quadratic assignment problems. Technical Report IDSIA-87-97, Dalle Molle Institute for Artificial Intelligence (1997)

    Google Scholar 

  3. Burkard, R.E., Karisch, S., Rendl, F.: Qaplib - a quadratic assignment problem library. European Journal of Operational Research 55, 115–119 (1991)

    Article  MATH  Google Scholar 

  4. Cela, E.: The Quadratic Assignment Problem. Combinatorial Optimizaiton, vol. 1. Kluwer Academic Publishers, Dordrecht (1998)

    MATH  Google Scholar 

  5. Misevicius, A.: A tabu search algorithm for the quadratic assignment problem. Computational Optimization And Applications 30, 95–111 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  6. Taillard, E.: Robust taboo search for the quadratic assignment problem. Parallel Computing 17, 443–455 (1991)

    Article  MathSciNet  Google Scholar 

  7. Gambardella, L., Taillard, E., Dorigo, M.: Ant colonies for the quadratic assignment problem. Journal of the Operational Research Society 50, 167–176 (1999)

    MATH  Google Scholar 

  8. Talbi, E., Roux, O., Fonlupt, C., Robillard, D.: Parallel ant colonies for the quadratic assignment problem. Future Generation Computer Systems 17, 441–449 (2001)

    Article  MATH  Google Scholar 

  9. Maniezzo, V., Colorni, A., Dorigo, M.: The ant system applied to the quadratic assignment. IEEE Transactions On Knowledge And Data Engineering 11, 769–778 (1999)

    Article  Google Scholar 

  10. Misevicius, A.: An improved hybrid genetic algorithm: new results for the quadratic assignment problem. Knowledge-Based Systems 17, 65–73 (2004)

    Article  Google Scholar 

  11. Oliveira, C.A., Pardalos, P.M., Resende, M.: Grasp with path-relinking for the quadratic assignment problem. In: Ribeiro, C.C., Martins, S.L. (eds.) WEA 2004. LNCS, vol. 3059, pp. 356–368. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  12. Misevicius, A.: A modified simulated annealing algorithm for the quadratic assignment problem. Informatica 14, 497–514 (2003)

    MATH  MathSciNet  Google Scholar 

  13. Mills, P., Tsang, E., Ford, J.: Applying an extended guided local search to the quadratic assignment problem. Annals Of Operations Research 118, 121–135 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  14. Hansen, P., Mladenović, N.: Variable neighborhood search: Principles and applications. European Journal of Operational Research 130, 449–467 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  15. Hansen, P., Mladenović, N.: Variable neighborhood search. Computers and Operations Research 24, 1097–1100 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  16. Hansen, P., Mladenović, N.: Handbook of Metaheuristics. In: Variable Neighborhood Search, pp. 621–757. Kluwer Academic Publishers, Dordrecht (2003)

    Google Scholar 

  17. García-López, F., Melián-Batista, B., Moreno-Pérez, J.A., Moreno-Vega, J.M.: The parallel variable neighborhood search for the p-median problem. Journal of Heuristics 8, 375–388 (2002)

    Article  MATH  Google Scholar 

  18. Mladenovic, N., Labbé, M., Hansen, P.: Solving the p-center problem with tabu search and variable neighborhood search. Networks 42, 48–64 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  19. Avanthay, C., Hertz, A., Zufferey, N.: A variable neighborhood search for graph coloring. European Journal Of Operational Research 151, 379–388 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  20. Bräysy, O.: A reactive variable neighborhood search for the vehicle-routing problem with time windows. Informs Journal On Computing 15, 347–368 (2003)

    Article  MathSciNet  Google Scholar 

  21. Bouthillier, A.L., Crainic, T.G.: A cooperative parallel meta-heuristic for the vehicle routing problem with time windows. Computers And Operations Research 32, 1685–1708 (2005)

    Article  MATH  Google Scholar 

  22. Drezner, Z.: The extended concentric tabu for the quadratic assignment problem. European Journal Of Operational Research 160, 416–422 (2005)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mathematical Sciences,  

    Chong Zhang, Zhangang Lin & Zuoquan Lin

  2. Key Laboratory of Pure and Applied Mathematics, Peking University, Beijing, 100871, China

    Chong Zhang, Zhangang Lin & Zuoquan Lin

Authors
  1. Chong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhangang Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zuoquan Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, C., Lin, Z., Lin, Z. (2005). Variable Neighborhood Search with Permutation Distance for QAP. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_12

Download citation

  • DOI: https://doi.org/10.1007/11554028_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28897-8

  • Online ISBN: 978-3-540-31997-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation