Skip to main content

Handling Preferences in the ”Pre-conflicting” Phase of Decision Making Processes under Multiple Criteria

  • Conference paper
Algorithmic Decision Theory (ADT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6992))

Included in the following conference series:

Abstract

Multiple criteria decision making (MCDM) literature concentrates on the concept of conflicting objectives, which is related to focusing on the need of trading off. Most approaches to eliciting preferences of the decision maker (DM) are built accordingly on contradistinguishing different attainable levels of objectives. We propose to pay attention to the non-conflicting aspects of decision making allowing the DM to express preferences as a desirable direction of consistent improvement of objectives. We show how such preference information combined with a dominance relation principle results in a Chebyshev-type scalarizing model, which can be used in early stages of decision making processes for deriving preferred solutions without trading off.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Branke, J., Deb, K., Miettinen, K., Slowinski, R. (eds.): Multiobjective Optimization: Interactive and Evolutionary Approaches. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  2. Deb, K., Miettinen, K., Chaudhuri, S.: Towards an Estimation of Nadir Objective Vector Using a Hybrid of Evolutionary and Local Search Approaches. IEEE Transactions on Evolutionary Computation 14(6), 821–841 (2010)

    Article  Google Scholar 

  3. Guerraggio, A., Molho, E.: The origins of quasi-concavity: a development between mathematics and economics. Historia Mathematica 31, 62–75 (2004)

    Article  MathSciNet  Google Scholar 

  4. Kaliszewski, I.: Qualitative Pareto analysis by cone separation technique. Kluwer Academic Publishers, Boston (1994)

    Book  Google Scholar 

  5. Kaliszewski, I.: Multiple criteria decision making: selecting variants along compromise lines. Techniki Komputerowe 1, 2006, 49–66 (2006)

    Google Scholar 

  6. Kaliszewski, I., Michalowski, W.: Efficient solutions and bounds on trade-offs. Journal of Optimization Theory and Applications 94, 381–394 (1997)

    Article  MathSciNet  Google Scholar 

  7. Miettinen, K.: Nonlinear Multiobjective Optimization. Kluwer Academic Publishers, Boston (1999)

    MATH  Google Scholar 

  8. Miettinen, K., Eskelinen, P., Ruiz, F., Luque, M.: NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point. European Journal of Operational Research 206, 426–434 (2010)

    Article  MathSciNet  Google Scholar 

  9. Miettinen, K., Mäkelä, M.M.: On scalarizing functions in multiobjective optimization. OR Spectrum 24, 193–213 (2002)

    Article  MathSciNet  Google Scholar 

  10. Miettinen, K., Ruiz, F., Wierzbicki, A.P.: Introduction to Multiobjective Optimization: Interactive Approaches. In: Branke, J., Deb, K., Miettinen, K., Słowiński, R. (eds.) Multiobjective Optimization. LNCS, vol. 5252, pp. 27–57. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  11. Podkopaev, D.: An approach to finding trade-off solutions by a linear transformation of objective functions. Control and Cybernetics 36(2), 347–356 (2007)

    MathSciNet  MATH  Google Scholar 

  12. Podkopaev, D.: Representing partial information on preferences with the help of linear transformation of objective space. In: Trzaskalik, T. (ed.) Multiple Criteria Decision Making 2007, pp. 175–194. The Karol Adamiecki University of Economics in Katowice Scientific Publications (2008)

    Google Scholar 

  13. Podkopaev, D.: Incorporating Explicit Tradeoff Information to Interactive Methods Based on the Chebyshev-type Scalarizing Function. Reports of the Department of Mathematical Information Technology. Series B: Scientific Computing. No. B9/2010. University of Jyväskylä, Jyväskylä (2010)

    Google Scholar 

  14. Ruiz, F., Luque, M., Miettinen, K.: Improving the computational efficiency in a global formulation (GLIDE) for interactive multiobjective optimization. Annals of Operations Research (2011), http://dx.doi.org/10.1007/s10479-010-0831-x

  15. Steuer, R.E.: Multiple Criteria Optimization: Theory, Computation and Application. Wiley Series in Probability and Mathematical Statistics. John Wiley, New York (1986)

    MATH  Google Scholar 

  16. Wierzbicki, A.P.: A mathematical basis for satisficing decision making. In: Morse, J.N. (ed.) Organizations: Multiple Agents with Multiple Criteria. LNEMS, vol. 190, pp. 465–485. Springer, Berlin (1981)

    Chapter  Google Scholar 

  17. Wierzbicki, A.P.: On the completeness and constructiveness of parametric characterization to vector optimization problems. OR Spectrum 8, 73–87 (1986)

    Article  MathSciNet  Google Scholar 

  18. Wierzbicki, A.P.: Multiple criteria solutions in noncooperative game theory, part III: theoretical foundations. Discussion Paper No. 288. Kyoto Institute of Economic Research (1990)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Podkopaev, D., Miettinen, K. (2011). Handling Preferences in the ”Pre-conflicting” Phase of Decision Making Processes under Multiple Criteria. In: Brafman, R.I., Roberts, F.S., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2011. Lecture Notes in Computer Science(), vol 6992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24873-3_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24873-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24872-6

  • Online ISBN: 978-3-642-24873-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics