Decisi-o-rama: An open-source Python library for multi-attribute value/utility decision analysis. (January 2021)

• Record Type: Journal Article
• Authors: Chacon-Hurtado, J.C.; Scholten, L.
• Is Part Of: Environmental modelling & software. Volume 135(2021)
• Publication Date: 2021-01
• Subjects: MAUT/MAVT -- Portfolio decision analysis -- Multi-criteria decision analysis -- Python; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104890
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Environmental decisions are complex as they are multi-dimensional, highly interdisciplinary and not only involve multiple stakeholders with conflicting objectives, but also many possible alternatives with uncertain consequences. The difficulty lies in making trade-offs between tough value trade-offs on the one hand while appreciating uncertain impacts of alternatives on the other. To support decisions tackling such problems, a combination of multi-criteria decision analysis (MCDA) and environmental models is promising yet limited by the available MCDA software. Here, we present Decisi-o-rama, an open-source Python MCDA library for single and sets (portfolios) of alternatives in the context of multi-attribute value/utility theory (MAUT/MAVT). Its development was driven by four aspirations that are crucial for usability in the context of environmental decision-making: (1) interoperability, (2) uncertainty-awareness, (3) computational efficiency, and (4) integration with portfolio decisions. The results indicate that these aspirations are met, thus facilitating the adoption of MCDA methods by environmental researchers and practitioners. Highlights: Decisi-o-rama is an open-source Python library for Multi-Criteria Decision Analysis (MCDA) to support environmental decisions. Decisi-o-rama supports uncertainty-aware MCDA in the context of MAUT/MAVT for single and portfolios of alternatives. Decisi-o-rama allows to quickly run large MCDA problems, supporting on-the-fly model exploration with decision makers. Decisi-o-rama is highly interoperable, allowing flexible use in concert with both simple or complex environmental models.