Aura: streamlit-based decision support software for sustainable multi-criteria decision-making

The Adaptive Utility Ranking Algorithm (AURA) is a Python-based decision support system designed to overcome the constraints of classical Multi-Criteria Decision-Making (MCDM) techniques such as TOPSIS and VIKOR. AURA combines benefit, cost, and target-type criteria in a single adaptive, distance-based scoring system, unlike the conventional methods which require different formulations of benefit and cost criteria and do not consider all criteria whose desired value is in the middle. In the case of target-type criteria, normalization is achieved by measuring the distance to a user-defined target value, where a proximity reward is given and deviation on either side are punished. The system also utilizes a tri-benchmark methodology comprising of the Positive Ideal Solution (PIS), Negative Ideal Solution (NIS), and the Average Solution (AVG) with a correction factor to increase stability and discrimination in ranking, which gives balanced and interpretable outcomes. AURA is developed in Python and Streamlit and offers a convenient interface to upload Excel decision matrices, allocate weights, and define criteria such as benefit, cost, and target. The software performs normalization, weighting, benchmark computation, and final scoring automatically and provides tabular and graphical output with downloadable reports. This methodology and software combination can be used to make AURA applicable in education and industry decision support. The peculiarity of AURA is the possibility to model situations of sustainability when trade-offs can often be achieved by fulfilling the desired goals instead of maximizing or minimizing extremes. AURA can be applied in the fields of business innovation, resource allocation, supply-chain analysis, and environmental management, allowing quick, transparent, and repeatable analyses. The system has high adaptability and commercialization capability, enabling eco-friendly, datadriven approaches and helping to achieve global sustainability objectives.