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Optimization in Science and Engineering pp 157–177Cite as

The Robustness Concern in Preference Disaggregation Approaches for Decision Aiding: An Overview

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Abstract

In multiple criteria decision aid, preference disaggregation techniques are used to facilitate the construction of decision models, through regression-based approaches that enable the elicitation of preferential information from a representative set of decision examples provided by a decision-maker. The robustness of such approaches and their results is an important feature for their successful implementation in practice. In this chapter we discuss the robustness concern in this context, overview the main methodologies that have been recently developed to obtain robust recommendations from disaggregation techniques, and analyze the connections with statistical learning theory, which is also involved with inferring models from data.

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Notes

  1. 1.

    The specification of the loss function L depends on the problem under consideration. For instance, in a regression setting it may correspond to the mean squared error, whereas in a classification context it may represent the accuracy rate.

  2. 2.

    Although this is not a restricted assumption, as the theory is general enough to accommodate other loss functions as well.

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Acknowledgements

This research has been co-financed by the European Union (European Social Fund) and Greek national funds through the Operational Program “Education and Lifelong Learning.”

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Authors and Affiliations

  1. School of Production Engineering and Management, Technical University of Crete, University Campus, 73100, Chania, Greece

    Michael Doumpos & Constantin Zopounidis

  2. Audencia Group, Nantes School of Management, Nantes, France

    Constantin Zopounidis

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  1. Michael Doumpos
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Correspondence to Michael Doumpos .

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Editors and Affiliations

  1. Department of Mathematics, National Technical University of Athens, Athens, Greece

    Themistocles M. Rassias

  2. Princeton University Dept. Chemical Engineering, Princeton, New Jersey, USA

    Christodoulos A. Floudas

  3. Dept. Industrial & Systems Engineering, Texas A&M University, College Station, Texas, USA

    Sergiy Butenko

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Doumpos, M., Zopounidis, C. (2014). The Robustness Concern in Preference Disaggregation Approaches for Decision Aiding: An Overview. In: Rassias, T., Floudas, C., Butenko, S. (eds) Optimization in Science and Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0808-0_8

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