Skip to main content
SpringerLink
Log in
Book cover

23rd International Conference on Soft Computing

MENDEL 2017: Recent Advances in Soft Computing pp 157–166Cite as

Stochastic Heuristics for Knapsack Problems

  • Conference paper
  • First Online:

  • 311 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 837))

Abstract

In this paper, we introduce knapsack problem formulations, discuss their time complexity and propose their representation and solution based on the instance size. First, deterministic methods are briefly summarized. They can be applied to small-size tasks with a single constraint. However, because of NP-completeness of the problem, more complex problem instances must be solved by means of heuristic techniques to achieve an approximation of the exact solution in a reasonable amount of time. The problem representations and parameter settings for a genetic algorithm and simulated annealing frameworks are shown.

This is a preview of subscription content, 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   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

Learn about institutional subscriptions

References

  1. Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman & Co., New York (1979)

    MATH  Google Scholar 

  2. Goldberg, D.E.: The Design of Innovation (Genetic Algorithms and Evolutionary Computation). Kluwer Academic Publishers, Dordrecht (2002)

    Google Scholar 

  3. Gulina, I., Matousek, R.: Efficient nearest neighbor searching in RRTs. In: Matousek, R. (ed.) Proceedings of 22nd International Conference on Soft Computing, MENDEL 2016 (2016)

    Google Scholar 

  4. Gutin, G., Punnen, A.P. (eds.): The Traveling Salesman Problem and Its Variations. Kluwer Academic Publishers, Dordrecht (2002)

    MATH  Google Scholar 

  5. Klapka, J., Dvořák, P., Popela, P.: Optimisation Methods. VUTIUM, Brno (2001). (in Czech)

    Google Scholar 

  6. Matousek, R., Popela, P.: Stochastic quadratic assignment problem: EV and EO reformulations solved by HC12. In: Proceedings of 20th International Conference on Soft Computing, MENDEL 2014. Brno University of Technology, VUT Press, Brno (2014)

    Google Scholar 

  7. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, Heidelberg (1996)

    MATH  Google Scholar 

  8. Michalewicz, Z., Fogel, D.B.: How to Solve It: Modern Heuristics. Springer, Berlin (2002)

    MATH  Google Scholar 

  9. Reeves, C.R.: Modern Heuristic Techniques for Combinatorial Problems. Blackwell Scientific Publications, Oxford (1993)

    MATH  Google Scholar 

  10. Šeda, M., Šeda, P.: A Minimisation of network covering services in a threshold distance. In: Matoušek, R. (ed.) Mendel 2015. Recent Advances in Soft Computing, vol. 378, pp. 159–169. Springer, Berlin (2015)

    Chapter  Google Scholar 

  11. Wolpert, D.H., McReady, W.G.: No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1, 67–82 (1997)

    Article  Google Scholar 

  12. Zelinka, I., Snášel, V., Abraham, A. (eds.): Handbook of Optimization. From Classical to Modern Approach. Springer, Berlin (2013)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 616 69, Brno, Czech Republic

    Miloš Šeda

  2. IBM Global Services Delivery Center, Technická 21, 616 00, Brno, Czech Republic

    Pavel Šeda

Authors
  1. Miloš Šeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pavel Šeda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miloš Šeda .

Editor information

Editors and Affiliations

  1. Department of Applied Computer Science, Institute of Automation and Computer Science, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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

Šeda, M., Šeda, P. (2019). Stochastic Heuristics for Knapsack Problems. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_14

Download citation

Publish with us

Policies and ethics

Search

Navigation