Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

A Decentralized Heuristic for Multiple-Choice Combinatorial Optimization Problems

  • Conference paper
  • First Online:
Operations Research Proceedings 2012

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

We present a decentralized heuristic applicable to multi-agent systems (MAS), which is able to solve multiple-choice combinatorial optimization problems (MC-COP). First, the MC-COP problem class is introduced and subsequently a mapping to MAS is shown, in which each class of elements in MC-COP corresponds to a single agent in MAS. The proposed heuristic “COHDA” is described in detail, including evaluation results from the domain of decentralized energy management systems.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Han, B., Leblet, J., Simon, G.: Hard multidimensional multiple choice knapsack problems, an empirical study. Computers & Operations Research 37(1), 172–181 (2010). doi:10.1016/j.cor.2009.04.006

    Article  Google Scholar 

  2. Hinrichs, C., Vogel, U., Sonnenschein, M.: Approaching Decentralized Demand Side Management via Self-Organizing Agents. In: Yolum, Tumer, Stone, Sonenberg (eds.) ATES Workshop, Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011). Taipei, Taiwan (2011).

    Google Scholar 

  3. Lust, T., Teghem, J.: The multiobjective multidimensional knapsack problem: a survey and a new approach. International Transactions in Operational Research 19(4), 495–520 (2012). doi:10.1111/j.1475-3995.2011.00840.x

  4. Martello, S., Toth, P.: Knapsack problems, 1 edn. John Wiley & Sons (1990).

    Google Scholar 

  5. Padhy, N.: Unit Commitment-A Bibliographical Survey. IEEE Transactions on Power Systems 19(2), 1196–1205 (2004). doi:10.1109/TPWRS.2003.821611

    Article  Google Scholar 

  6. Pisinger, D.: A minimal algorithm for the multiple-choice knapsack problem. European Journal of Operational Research 83(2), 394–410 (1995).doi:10.1016/0377-2217(95)00015-I

    Google Scholar 

  7. Pisinger, D.: Linear Time Algorithms for Knapsack Problems with Bounded Weights. Journal of Algorithms 33(1), 1–14 (1999). doi:10.1006/jagm.1999.1034

    Google Scholar 

  8. Strogatz, S.H.: Exploring complex networks. Nature 410(6825), 268–276 (2001). doi:10.1038/35065725

    Article  Google Scholar 

  9. Talbi, E.G.: Metaheuristics. John Wiley & Sons, Inc., Hoboken, NJ, USA (2009). 10.1002/9780470496916.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Oldenburg, Oldenburg, Germany

    Christian Hinrichs & Michael Sonnenschein

  2. OFFIS, Institute for Information Technology, Oldenburg, Germany

    Sebastian Lehnhoff

Authors
  1. Christian Hinrichs
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sebastian Lehnhoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael Sonnenschein
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christian Hinrichs .

Editor information

Editors and Affiliations

  1. Institute of Production Management, Leibniz Universität Hannover, Hannover, Germany

    Stefan Helber

  2. Institute for Information Systems Resear, Leibniz Universität Hannover, Hannover, Germany

    Michael Breitner

  3. Institute for Banking and Finance, Leibniz Universität Hannover, Hannover, Germany

    Daniel Rösch

  4. Institute of Production Management, Leibniz Universität Hannover, Hannover, Germany

    Cornelia Schön

  5. Institute for Risk and Insurance, Leibniz Universität Hannover, Hannover, Germany

    Johann-Matthias Graf von der Schulenburg

  6. Institute of Statistics, Leibniz Universität Hannover, Hannover, Germany

    Philipp Sibbertsen

  7. Institute of Applied Mathematics, Leibniz Universität Hannover, Hannover, Germany

    Marc Steinbach

  8. Institute of Probability and Statistics, Leibniz Universität Hannover, Hannover, Germany

    Stefan Weber

  9. Institute of Production Management, Leibniz Universität Hannover, Hannover, Germany

    Anja Wolter

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Hinrichs, C., Lehnhoff, S., Sonnenschein, M. (2014). A Decentralized Heuristic for Multiple-Choice Combinatorial Optimization Problems. In: Helber, S., et al. Operations Research Proceedings 2012. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-00795-3_43

Download citation

Publish with us

Policies and ethics

Search

Navigation