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NAUTILUS framework: towards trade-off-free interaction in multiobjective optimization

Author

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  • Kaisa Miettinen

    (University of Jyvaskyla, Department of Mathematical Information Technology)

  • Francisco Ruiz

    (Universidad de Málaga)

Abstract

In this paper, we present a framework of different interactive NAUTILUS methods for multiobjective optimization. In interactive methods, the decision maker iteratively sees solution alternatives and provides one’s preferences in order to find the most preferred solution. We question the widely used setting that the solutions shown to the decision maker should all be Pareto optimal which implies that improvement in any objective function necessitates allowing impairment in some others. Instead, in NAUTILUS we enable the decision maker to make a free search without having to trade-off by starting from an inferior solution and iteratively approaching the Pareto optimal set by allowing all objective functions to improve. The framework presented consists of different modules for preference elicitation and optimization. Four main NAUTILUS method variants are introduced as well as ideas of utilizing the framework in a flexible way to derive further variants.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jbecon:v:86:y:2016:i:1:d:10.1007_s11573-015-0786-0
    DOI: 10.1007/s11573-015-0786-0
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    References listed on IDEAS

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    1. Abel, Ami & Korhonen, Pekka, 1996. "Using aspiration levels in an interactive interior multiobjective linear programming algorithm," European Journal of Operational Research, Elsevier, vol. 89(1), pages 193-201, February.
    2. 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.
    3. 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..
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Ruiz, Ana B. & Sindhya, Karthik & Miettinen, Kaisa & Ruiz, Francisco & Luque, Mariano, 2015. "E-NAUTILUS: A decision support system for complex multiobjective optimization problems based on the NAUTILUS method," European Journal of Operational Research, Elsevier, vol. 246(1), pages 218-231.
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    Cited by:

    1. Eyvindson, Kyle & Repo, Anna & Mönkkönen, Mikko, 2018. "Mitigating forest biodiversity and ecosystem service losses in the era of bio-based economy," Forest Policy and Economics, Elsevier, vol. 92(C), pages 119-127.
    2. 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.
    3. Bhupinder Singh Saini & Michael Emmerich & Atanu Mazumdar & Bekir Afsar & Babooshka Shavazipour & Kaisa Miettinen, 2022. "Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations," Journal of Global Optimization, Springer, vol. 83(4), pages 865-889, August.
    4. Maciej Nowak & Tadeusz Trzaskalik, 2022. "A trade-off multiobjective dynamic programming procedure and its application to project portfolio selection," Annals of Operations Research, Springer, vol. 311(2), pages 1155-1181, April.

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    More about this item

    Keywords

    Interactive methods; Multicriteria optimization; Pareto optimality;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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