Skip to main content

A Comparative Study of Exploration Ability of Harmony Search Algorithms

  • Conference paper
  • First Online:
Harmony Search Algorithm (ICHSA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 514))

Included in the following conference series:

  • 732 Accesses

Abstract

Harmony Search Algorithm (HSA) is one of the efficient optimization algorithms among various optimization algorithms proposed over the years. In literature, many variants of the Harmony search algorithms are proposed based on the various ideas. In this article the exploration ability of the four HS algorithms are compared. An experimental comparative study of exploration ability of different versions of HS algorithms is done. The article provides a detailed explorative abilities of various HS algorithms. The comparison is based on the theoretical studies performed inĀ [1]. The theoretical conclusions of the exploration analysis are justified with experimental studies. This article concludes with the searching ability of various HS algorithms along with their ranking with most explorative HS algorithm.

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

Access this chapter

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 EPUB and 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

References

  1. Das, S., Mukhopadhyay, A., Roy, A., Abraham, A., Panigrahi, B.K.: Exploratory power of the harmony search algorithm: analysis and improvements for global numerical optimization. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41(1), 89ā€“106 (2011)

    ArticleĀ  Google ScholarĀ 

  2. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60ā€“68 (2001)

    ArticleĀ  Google ScholarĀ 

  3. Mahdavi, M., Fesanghary, M., Damangir, E.: An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 188(2), 1567ā€“1579 (2007)

    MathSciNetĀ  MATHĀ  Google ScholarĀ 

  4. Omran, M.G.H., Mahdavi, M.: Global-best harmony search. Appl. Math. Comput. 198(2), 643ā€“656 (2008)

    MathSciNetĀ  MATHĀ  Google ScholarĀ 

  5. Pan, Q.K., Suganthan, P.N., Tasgetiren, M.F., Liang, J.J.: A self-adaptive global best harmony search algorithm for continuous optimization problems. Appl. Math. Comput. 216(3), 830ā€“848 (2010)

    MathSciNetĀ  MATHĀ  Google ScholarĀ 

  6. Yadav, A., Deep, K.: Shrinking hypersphere based trajectory of particles in PSO. Appl. Math. Comput. 220, 246ā€“267 (2013)

    MATHĀ  Google ScholarĀ 

  7. Yadav, A., Deep, K.: An efficient co-swarm particle swarm optimization for non-linear constrained optimization. J. Comput. Sci. 5(2), 258ā€“268 (2014)

    ArticleĀ  Google ScholarĀ 

  8. Yadav, A., Deep, K., Kim, J.H., Nagar, A.K.: Gravitational swarm optimizer for global optimization. Swarm Evol. Comput. 31, 64ā€“89 (2016)

    ArticleĀ  Google ScholarĀ 

  9. Yadav, A., Yadav, N., Kim, J.H.: A study of harmony search algorithms: exploration and convergence ability. In: Kim, J.H., Geem, Z.W. (eds.) ICHSA2015. AISC, vol. 382, pp. 53ā€“62. Springer, Heidelberg (2016). doi:10.1007/978-3-662-47926-1_6

    ChapterĀ  Google ScholarĀ 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joong Hoon Kim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

Ā© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Yadav, A., Yadav, N., Kim, J.H. (2017). A Comparative Study of Exploration Ability of Harmony Search Algorithms. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3728-3_4

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3727-6

  • Online ISBN: 978-981-10-3728-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics