Skip to main content

Cuckoo Search: From Continuous to Combinatorial

  • Chapter
  • First Online:
Discrete Cuckoo Search for Combinatorial Optimization

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

When solving combinatorial optimization problems with nature-inspired metaheuristics (which are mostly initiated in continuous spaces), the first constraint to manage is how to move in the combinatorial space of solutions without affecting the performance of these metaheuristics. The definition of the neighborhood of a solution in space represents a second constraint.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and 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
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

  • Bak P (1997) How nature works. Oxford University Press, Oxford

    MATH  Google Scholar 

  • Brown CT, Liebovitch LS, Glendon R (2007) Lévy flights in dobe ju/?hoansi foraging patterns. Human Ecol 35(1):129–138

    Article  Google Scholar 

  • Fister I Jr, Yang X-S, Fister D, Fister I (2014) Cuckoo search: a brief literature review. In: Cuckoo search and firefly algorithm. Springer, pp 49–62

    Google Scholar 

  • Gandomi AH, Talatahari S, Yang X-S, Deb S (2012) Design optimization of truss structures using cuckoo search algorithm. In: The structural design of tall and special buildings

    Google Scholar 

  • Gandomi AH, Yang X-S, Alavi AH (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29(1):17–35

    Article  Google Scholar 

  • Geem ZW, Kim JH et al (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60–68

    Article  Google Scholar 

  • Ouaarab A, Ahiod B, Yang X-S (2014) Discrete cuckoo search algorithm for the travelling salesman problem. Neural Comput Appl 24(7–8):1659–1669

    Article  Google Scholar 

  • Payne RB, Sorenson MD (2005) The cuckoos, vol 15. Oxford University Press, USA

    Google Scholar 

  • Reynolds AM, Frye MA (2007) Free-flight odor tracking in drosophila is consistent with an optimal intermittent scale-free search. PLoS One 2(4):e354

    Article  Google Scholar 

  • Shlesinger MF, Zaslavsky GM, Frisch U (1995) Lévy flights and related topics in physics. In: Levy flights and related topics in physics, vol 450

    Google Scholar 

  • Srivastava PR, Varshney A, Nama P, Yang X-S (2012) Software test effort estimation: a model based on cuckoo search. Int J Bio-Inspired Comput 4(5):278–285

    Article  Google Scholar 

  • Viswanathan G, Buldyrev S, Havlin S, Da Luz M, Raposo E, Stanley H (1999) Optimizing the success of random searches. Nature 401(6756):911–914

    Article  Google Scholar 

  • Yang C, Wang L, Liang W, Møller AP (2017) How cuckoos find and choose host nests for parasitism. Behav Ecol 28(3):859–865

    Article  Google Scholar 

  • Yang X-S, Deb S (2009) Cuckoo search via lévy flights. In: World congress on nature and biologically inspired computing, 2009. NaBIC 2009. IEEE, pp 210–214

    Google Scholar 

  • Yang XS, Deb S (2010) Engineering optimisation by cuckoo search. Int J Math Model Numer Optim 1(4):330–343

    MATH  Google Scholar 

  • Yang X-S, Deb S (2013) Multiobjective cuckoo search for design optimization. Comput Oper Res 40:1616–1624

    Article  MathSciNet  Google Scholar 

  • Yang X-S, Deb S (2014) Cuckoo search: recent advances and applications. Neural Comput Appl 24(1):169–174

    Article  Google Scholar 

  • Yang X-S, Deb S, Karamanoglu M, He X (2012) Cuckoo search for business optimization applications

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aziz Ouaarab .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ouaarab, A. (2020). Cuckoo Search: From Continuous to Combinatorial. In: Discrete Cuckoo Search for Combinatorial Optimization. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-3836-0_4

Download citation

Publish with us

Policies and ethics