Multiobjective Optimization-Based Collective Opinion Generation With Fairness Concern

doi:10.1109/TSMC.2023.3273715

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Multiobjective Optimization-Based Collective Opinion Generation With Fairness Concern

2023-09-01

Enrique Herrera‐Viedma

Mirosław J. Skibniewski

DOI：10.1109/TSMC.2023.3273715

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Abstract

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The generation of collective opinion based on probability distribution function (PDF) aggregation is gradually becoming a critical approach for tackling immense and delicate assessment and evaluation tasks in decision analysis. However, the existing collective opinion generation approaches fail to model the behavioral characteristics associated with individuals, and thus, cannot reflect the fairness concerns among them when they consciously or unconsciously incorporate their judgments on the fairness level of distribution into the formulations of individual opinions. In this study, we propose a multiobjective optimization-driven collective opinion generation approach that generalizes the bi-objective optimization-based PDF aggregation paradigm. In doing so, we adapt the notion of fairness concern utility function to characterize the influence of fairness inclusion and take its maximization as an additional objective, together with the criteria of consensus and confidence levels, to achieve in generating collective opinion. The formulation of fairness concern is then transformed into the congregation of individual fairness concern utilities in the use of aggregation functions. We regard the generalized extended Bonferroni mean (BM) as an elaborated framework for aggregating individual fairness concern utilities. In such way, we establish the concept of BM-type collective fairness concern utility to empower multiobjective optimization-driven collective opinion generation approach with the capacity of modeling different structures associated with the expert group with fairness concern. The application of the proposed fairness-aware framework in the maturity assessment of building information modeling demonstrates the effectiveness and efficiency of multiobjective optimization-driven approach for generating collective opinion when accomplishing complicated assessment and evaluation tasks with data scarcity.

Keywords:

Behavioral sciences

Optimization

Task analysis

Probability distribution

Bayes methods

Probabilistic logic

Probability density function

Collective opinion generation

fairness concern

multiobjective optimization

probability distribution function (PDF)