A regret-based query selection strategy for the incremental elicitation of the criteria weights in an SRMP model

Arwa Khannoussi (), Alexandru-Liviu Olteanu (), Patrick Meyer () and Nawal Benabbou ()
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Arwa Khannoussi: IMT Atlantique, LS2N, UMR CNRS 6004
Alexandru-Liviu Olteanu: Université Bretagne Sud.
Patrick Meyer: IMT Atlantique, Lab-STICC, UMR CNRS 6285
Nawal Benabbou: Sorbonne Université, LIP6

Operational Research, 2024, vol. 24, issue 2, No 1, 21 pages

Abstract: Abstract SRMP, which stands for “Simple Ranking with Multiple Profiles”, is a Multi-Criteria Decision Aiding model aiming to rank alternatives according to the preferences of a Decision Maker (DM) using reference criteria evaluations. Determining the preference parameters of SRMP can be tiring for the DM, who is often asked to compare several alternatives pairwisely during a preference elicitation process. It has been proposed in the literature to use an incremental elicitation process which selects informative pairs of alternatives which are submitted to the DM in sequence. The goal in such a process is to refine the SRMP model at each iteration, until a robust recommendation is determined, while limiting the cognitive effort of the DM. In this research, using a regret-based elicitation approach, we present a new heuristic for choosing the pairs of alternatives sequentially submitted for evaluation to the DM. We also provide a mixed-integer linear program for an efficient computation of regret values in practice. We limit our solution to the elicitation of the criteria weights, a subset of the SRMP model’s parameters, and we demonstrate that in this setting, the suggested heuristic outperforms previously examined query selection algorithms.

Keywords: Multi-criteria decision aiding; Incremental preference elicitation; Query selection strategy; Regret-based approach; 91B06; 91B08; 65L12; 90C11 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12351-024-00823-y

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