Skip to main content
SpringerLink
Log in

Harmony Search with Teaching-Learning Strategy for 0-1 Optimization Problem

  • Conference paper
  • First Online:
Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 891))

  • 705 Accesses

Abstract

0-1 optimization problem plays an important role in operational research. In this paper, we use a recently proposed algorithm named harmony search with teaching-learning (HSTL) strategy which derived from Teaching-Learning-Based Optimization (TLBO) for solving. Four strategies (Harmony memory consideration, teaching-learning strategy, local pitch adjusting and random mutation) are employed to improve the performance of HS algorithm. Numerical results demonstrated very good computational performance.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

References

  1. Dantzig, G.B., Fulkerson, D.R., Johnson, S.M.: Solution of a large-scale traveling salesman problem. Oper. Res. 2, 393–410 (1954)

    MathSciNet  Google Scholar 

  2. Gomory, R.E.: Outline of an algorithm for integer solutions to linear programs. Bull. Am. Math. Soc. 64, 275–278 (1958)

    Article  MathSciNet  Google Scholar 

  3. Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. Wiley, New York (1988)

    Book  Google Scholar 

  4. Barnhart, C., Johnson, E.L., Nemhauser, G.L., et al.: Branch-and-price: column generation forsolving huge integer programs. Oper. Res. 48, 316–329 (1998)

    Article  Google Scholar 

  5. Wolsey, L.A.: Integer Programming. Wiley, New York (1998)

    MATH  Google Scholar 

  6. Jiinger, M., Liebling, T., Naddef, D., et al.: 50 Years of Integer Programming 1958-2008: From the Early Years to the State-of-the-Art. Springer, Berlin (2010)

    Book  Google Scholar 

  7. Li, D., Sun, X.L.: Nonlinear Integer Programming. Springer, New York (2006)

    MATH  Google Scholar 

  8. Jourdan, L., Basseur, M., Talbi, E.G.: Hybridizing exact methods and metaheuristics: a taxonomy. Eur. J. Oper. Res. 199(3), 620–629 (2009)

    Article  MathSciNet  Google Scholar 

  9. Zong, W.G., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simul. Trans. Soc. Model. Simul. Int. 76(2), 60–68 (2001)

    Google Scholar 

  10. Zhao, X., Liu, Z., Hao, J., et al.: Semi-self-adaptive harmony search algorithm. Nat. Comput. 16(4), 1–18 (2017)

    Article  MathSciNet  Google Scholar 

  11. Yong, L., Liu, S., Zhang, J., Feng, Q.: Theoretical and empirical analyses of an improved harmony search algorithm based on differential mutation operator. J. Appl. Math. 2012, Article ID 147950

    Google Scholar 

  12. Tuo, S., Yong, L., Zhou, T.: An improved harmony search based on teaching-learning strategy for unconstrained optimization problems. Math. Probl. Eng. 2013, Article ID 413565, 29 pages. https://doi.org/10.1155/2013/413565

    Article  Google Scholar 

  13. Tuo, S., Yong, L., Deng, F.: A novel harmony search algorithm based on teaching-learning strategies for 0-1 knapsack problems. Sci. World J. 2014, Article ID 637412, 19 pages. https://doi.org/10.1155/2014/637412

    Article  Google Scholar 

  14. Tuo, S., Zhang, J., Yong, L., Yuan, X.: A harmony search algorithm for high-dimensional multimodal optimization problems. Digit. Signal Process. Rev. J. 46(11), 151–163 (2015)

    Article  MathSciNet  Google Scholar 

  15. Tuo, S., Yong, L., et al.: HSTLBO: a hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems. PLoS ONE 12, e0175114 (2017)

    Article  Google Scholar 

  16. Wang, L., Hu, H., Liu, R., et al.: An improved differential harmony search algorithm for function optimization problems. Soft. Comput. 4, 1–26 (2018)

    Google Scholar 

  17. Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf. Sci. 183(1), 1–15 (2012)

    Article  MathSciNet  Google Scholar 

  18. Rao, R.V., Savsani, V.J., Balic, J.: Teaching-learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems. Eng. Optim. 44(12), 1447–1462 (2012)

    Article  Google Scholar 

  19. Pardalos, P.M.: Construction of test problems in quadratic bivalent programming. ACM Trans. Math. Softw. 17(1), 74–87 (1991)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgment

This work is supported by Project of Youth Star in Science and Technology of Shaanxi Province (2016KJXX-95)

Author information

Authors and Affiliations

  1. School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong, 723001, China

    Longquan Yong

Authors
  1. Longquan Yong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Longquan Yong .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Pavel Krömer

  2. School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, China

    Hong Zhang

  3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Yongquan Liang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yong, L. (2019). Harmony Search with Teaching-Learning Strategy for 0-1 Optimization Problem. In: Krömer, P., Zhang, H., Liang, Y., Pan, JS. (eds) Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2018. Advances in Intelligent Systems and Computing, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-03766-6_32

Download citation

Publish with us

Policies and ethics

Search

Navigation