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

Michael Doumpos () and Constantin Zopounidis ()
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Michael Doumpos: Technical University of Crete, School of Production Engineering and Management
Constantin Zopounidis: Technical University of Crete, School of Production Engineering and Management

A chapter in Optimization in Science and Engineering, 2014, pp 157-177 from Springer

Abstract: 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.

Keywords: Robustness Concern; Decision Examples; Multiple Criteria Decision Aid (MCDA); Marginal Value Functions; Ordinal Regression Setting (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4939-0808-0_8

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DOI: 10.1007/978-1-4939-0808-0_8

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