期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 135, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2020.104890
关键词
MAUT/MAVT; Portfolio decision analysis; Multi-criteria decision analysis; Python
类别
资金
- NWO domain TTW (the domain applied and Engineering Sciences of the Netherlands Organisation for Scientific Research) [15343]
- RIONED Foundation
- STOWA (Foundation for Applied Water Research)
- Knowledge Program Urban Drainage (KPUD)
Environmental decisions are complex due to their multidimensional nature, involving multiple stakeholders and uncertain consequences. Decisi-o-rama, an open-source Python MCDA library, addresses the challenges by focusing on usability, uncertainty awareness, computational efficiency, and integration with portfolio decisions, facilitating the adoption of MCDA methods in environmental decision-making.
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.
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