Skip to main content

Abstract

Genetic algorithm (GA) is an optimization algorithm that is often categorized as a global search heuristic technique. Being a branch of evolutionary computation, it is known to mimic the natural selection of biological processes of reproduction and to solve the ‘fittest’ solutions. In this chapter, the knapsack problem was solved using GA technique to determine the strength or capacity of bag used in convey items. The solution of the model shows that no combination of any form would give an exact weight or capacity the bag can carry except set spaces 15 and 29, where the weight of items are 34 kg and 36 kg respectively. Hence the feasible weight of item to be stored in the bag is 34 kg at a value of 16. Any weight of material above 36 kg will lead to the ripping of the bag.

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
Hardcover Book
USD 169.99
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

  1. Simon, D. 2013. Evolutionary optimization algorithms: Biologically inspired and population-based approaches to computer intelligence. Hoboken: Wiley.

    MATH  Google Scholar 

  2. Raymer, M.L., W.F. Punch, E.D. Goodman, L.A. Kuhn, and A.K. Jain. 2000. Dimensionality reduction using genetic algorithms. IEEE Transactions on Evolutionary Computation 4 (2): 164–171.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Modestus O. Okwu .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Okwu, M.O., Tartibu, L.K. (2021). Genetic Algorithm. In: Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications. Studies in Computational Intelligence, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-61111-8_13

Download citation

Publish with us

Policies and ethics