A New Paradigm for Multicriteria Decision Making

In this framework, Pareto‑efficiency is an important property, but the novelty lies in maximizing the performance index, which yields a clear guarantee against all plausible weightings—making the choice defensible without requiring agreement on the weights. The analysis develops a simple performance index that reveals the tradeoffs between criteria and selects a defensible option even when stakeholders disagree on priorities. The method requires only continuity of criteria and compactness of the feasible set (and thus also applies to discrete/non‑convex problems).

Beyond weight ambiguity, the framework also accommodates other forms of uncertainty: criterion ambiguity (uncertain criterion values) and aggregation ambiguity (uncertainty about how to combine criteria into a single score). These extensions yield transparent decisions with verifiable guarantees in the presence of multiple, layered ambiguities.

Illustrative applications include energy policy (security–equity–sustainability), QALY‑based health evaluations, and corporate resource allocation—contexts where priorities shift and weights are hard to justify, yet robust tradeoff management is essential.

The paper, titled “Relatively Robust Multicriteria Decisions,” by Prof. Thomas A. Weber (Chair of Operations, Economics and Strategy, EPFL), was published online in Management Science (Articles in Advance) on August 14, 2025. It was presented at the 18th INFORMS Computing Society (ICS) Conference, Toronto, Canada, March 14–16, 2025; at EURO 2025 — the 34th European Conference on Operational Research, University of Leeds, UK, June 22–25, 2025; and earlier in preliminary form at the 27th International Conference on Multiple Criteria Decision Making (MCDM 2024), Hammamet, Tunisia, June 2–7, 2024.

Abstract

For a general multicriteria decision problem with linear scalarization and unknown weights, we propose relatively robust decisions, which are Pareto-efficient and at the same time maximize a performance index. The latter measures the worst-case ratio, attained by the weighted objective relative to its maximum value, with respect to all possible weights. The main results include a simple boundary representation of the performance index as the minimum of criterion-specific performance ratios, and a computationally simple method of determining a relatively robust decision up to any prespecified performance tolerance by maximizing an epsilon-augmented performance index. The proposed method relies merely on the continuity of all criterion functions and the compactness of the set of feasible decisions which may be nonconvex. This imposes no restrictions at all for any finite action set. A notable feature of our method is that it endogenously yields the tradeoffs between all criteria, including a performance guarantee relative to decisions justified by any other weighting. A number of structural results, examples, and applications are provided, as well as generalizations to allow for limited weight ambiguity, criterion ambiguity, and generalized aggregation of criteria based on an axiomatic foundation.