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A new preference handling technique for interactive multiobjective optimization without trading-off

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  • Kaisa Miettinen
  • Dmitry Podkopaev
  • Francisco Ruiz
  • Mariano Luque

Abstract

Because the purpose of multiobjective optimization methods is to optimize conflicting objectives simultaneously, they mainly focus on Pareto optimal solutions, where improvement with respect to some objective is only possible by allowing some other objective(s) to impair. Bringing this idea into practice requires the decision maker to think in terms of trading-off, which may limit the ability of effective problem solving. We outline some drawbacks of this and exploit another idea emphasizing the possibility of simultaneous improvement of all objectives. Based on this idea, we propose a technique for handling decision maker’s preferences, which eliminates the necessity to think in terms of trade-offs. We incorporate this technique into an interactive trade-off-free method for multiobjective optimization. We call the resulting method NAUTILUS 2, which is also suitable for negotiation support. We demonstrate the applicability of the new method with an example problem. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Kaisa Miettinen & Dmitry Podkopaev & Francisco Ruiz & Mariano Luque, 2015. "A new preference handling technique for interactive multiobjective optimization without trading-off," Journal of Global Optimization, Springer, vol. 63(4), pages 633-652, December.
    • Handle: RePEc:spr:jglopt:v:63:y:2015:i:4:p:633-652
    DOI: 10.1007/s10898-015-0301-8
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    References listed on IDEAS

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    1. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
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    4. Francisco Ruiz & Mariano Luque & Kaisa Miettinen, 2012. "Improving the computational efficiency in a global formulation (GLIDE) for interactive multiobjective optimization," Annals of Operations Research, Springer, vol. 197(1), pages 47-70, August.
    5. Aloysius, John A. & Davis, Fred D. & Wilson, Darryl D. & Ross Taylor, A. & Kottemann, Jeffrey E., 2006. "User acceptance of multi-criteria decision support systems: The impact of preference elicitation techniques," European Journal of Operational Research, Elsevier, vol. 169(1), pages 273-285, February.
    6. Ehtamo, Harri & Kettunen, Eero & Hamalainen, Raimo P., 2001. "Searching for joint gains in multi-party negotiations," European Journal of Operational Research, Elsevier, vol. 130(1), pages 54-69, April.
    7. Luque, Mariano & Miettinen, Kaisa & Eskelinen, Petri & Ruiz, Francisco, 2009. "Incorporating preference information in interactive reference point methods for multiobjective optimization," Omega, Elsevier, vol. 37(2), pages 450-462, April.
    8. Miettinen, Kaisa & Eskelinen, Petri & Ruiz, Francisco & Luque, Mariano, 2010. "NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point," European Journal of Operational Research, Elsevier, vol. 206(2), pages 426-434, October.
    9. J. Cabello & M. Luque & F. Miguel & A. Ruiz & F. Ruiz, 2014. "A multiobjective interactive approach to determine the optimal electricity mix in Andalucía (Spain)," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 109-127, April.
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    Cited by:

    1. Ana B. Ruiz & Francisco Ruiz & Kaisa Miettinen & Laura Delgado-Antequera & Vesa Ojalehto, 2019. "NAUTILUS Navigator: free search interactive multiobjective optimization without trading-off," Journal of Global Optimization, Springer, vol. 74(2), pages 213-231, June.
    2. Kaisa Miettinen & Francisco Ruiz, 2016. "NAUTILUS framework: towards trade-off-free interaction in multiobjective optimization," Journal of Business Economics, Springer, vol. 86(1), pages 5-21, January.
    3. Piercy, Craig A. & Steuer, Ralph E., 2019. "Reducing wall-clock time for the computation of all efficient extreme points in multiple objective linear programming," European Journal of Operational Research, Elsevier, vol. 277(2), pages 653-666.

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