Unique Preference Aggregation in Design and Decision Making

TL;DR

This paper introduces a rigorous, unique preference aggregation framework based on measurement theory, addressing limitations of existing methods in multi-criteria decision analysis and design optimization.

Contribution

It establishes the principal axioms for unique preference aggregation, providing a mathematically valid foundation that improves robustness in decision-making and optimization.

Findings

Common aggregation methods often produce inconsistent rankings.

The proposed framework clarifies the limits of valid aggregation.

It offers a principled basis for robust MCDA and MODO.

Abstract

Preference aggregation is a core operation in multi-objective design optimisation and group decision-making, as it determines the best-fit-for-common-purpose alternative within complex socio-technical contexts. Therefore, their aggregation requires a rigorous measurement-theoretic foundation to ensure mathematical validity, interpretability, and uniqueness. PFM establishes the principal axioms of unique preference aggregation, providing a rigorous basis on which aggregation can be demonstrated. In this paper, it is shown that commonly used aggregation approaches in MCDM - such as weighted arithmetic and geometric means, as well as weighted distance-based optimisation methods - often fail to produce consistent rankings and are therefore unsuitable for pure MCDM. In contrast, the unique preference aggregation presented here clarifies the mathematical limits of valid aggregation and provides a principled, implementable foundation for robust multi-criteria decision analysis (MCDA) and multi-objective design optimisation (MODO) in multi-faceted problems.