Building Decision Support Systems based on Fuzzy Inference

Uncertainty and ambiguity are inherent properties of our understanding of the world and our ability to communicate this understanding to others, in both a quantitative and qualitative way. This fact makes uncertainty and ambiguity inherent in decision making processes and thus decision support tools need to provide capabilities for their effective handling. This paper presents an overview of a number of decision support systems, integrating quantitative and qualitative criteria, primarily by means of fuzzy inference as a tool for handling linguistic ambiguity and uncertainty. The decision support systems discussed cover a wide range of spatial scales, from local to regional, a number of different contexts, from urban to rural and address a variety of objectives, from urban sustainability to regional environmental protection. They have all been developed in the Urban Water Research Group of the Civil and Environmental Engineering Department at Imperial College London, over a period of 10 years. Despite their differences, the models discussed possess common underlying methodological concepts and have been developed to some extent with similar “building blocks”. Issues of complementarities and added value which result from both the conceptual and methodological approaches adopted are explored and an indication of possible future directions is presented. It is concluded that a flexible, component-based, rapid-prototyping method for developing decision support systems capable of explicit handling of ambiguity and uncertainty through fuzzy inference are fundamental to the development of tools, which can be adopted in practice and can truly support inclusive decision making.