Helping to Choose a Robust Alternative: A Sensitivity Analysis and a Software Tool for Multi‐Criteria Decision‐Making

ABSTRACT Multicriteria decision‐making (MCDM) often involves evaluating or ranking alternatives on multiple attributes, a process that is far from trivial due to flexible preferences and uncertainty in the criteria importance. The recently proposed W eightless, I nterval‐ B ased A pproach (WIBA) tackles these issues by relying on an ordering of the criteria (according to their relevance) instead of explicit weights and using interval scores to evaluate alternatives. Although originally proposed for selecting solutions of interest in the context of multi‐objective and many objective optimization problems, it can be adapted to rank such solutions. However, the robustness of WIBA rankings has not been studied, and sensitivity analysis approaches based on perturbations of the weights cannot be applied. Furthermore, there is no friendly environment for exploring WIBA properties. This paper addresses these gaps by (1) introducing a novel local sensitivity analysis technique to explore how small perturbations in the order of criteria affect rankings, and (2) presenting WIBApp, a freely available visual software tool that implements WIBA features, including the proposed sensitivity analysis. Using a case study on the selection of technical universities, the paper first illustrates WIBA's flexibility and utility in real‐world decision scenarios, enabling decision makers to effectively deal with uncertainty and complexity, and second shows how WIBApp simplifies data management, enhances analysis and facilitates comparisons among rankings. By advancing the theoretical foundations of WIBA and providing a practical implementation, this work contributes to providing decision makers with a robust framework for handling multi‐criteria problems, enhancing the reliability of rankings and supporting informed decisions.