Model-Based Decision Support for Industry-Environment Interactions

Applied systems analysis is -- or should be -- a tool in the hands of planners and decision makers who have to deal with the complex and growing problems of modern society. There is, however, an obvious gap between the ever-increasing complexity and volume of scientific and technological information and tools of analysis relevant to large socio-technical and environmental systems, and the information requirements at a strategic planning and policy level. The Advanced Computer Applications (ACA) project builds on IIASA's traditional strength in the methodological foundations of operations research and applied systems analysis, and its rich experience in numerous application areas including the environment, technology, and risk. The ACA group draws on this infrastructure and combines it with elements of AI and advanced information and computer technology. Several completely externally-funded research and development projects in the field of model-based decision support and applied Artificial Intelligence (AI) are currently under way. As an example of this approach to information and decision support systems, one of the components of an R&D project sponsored by the CEC's EURATOM Joint Research Centre (JRC) at Ispra, Italy, in the area of hazardous substances and industrial risk management, is described in this paper. The PDA (Production Distribution Area) is an interactive optimization code (based on DIDASS, one of a family of multicriteria decision support tools developed at IIASA) and a linear problem solver, for chemical industry structures, configured for the pesticide industry of a hypothetical region. The user can select optimization criteria, define allowable ranges or constraints on these criteria, define reference points for the multi-criteria trade-off, and display various levels of model output, including the waste streams generated by the different industrial structure alternatives. These waste streams can then be used to provide input conditions for the environmental impact models. With the emphasis on a directly understandable problem representation and dynamic color graphics, and the user interface as a key element of interactive decision support systems, this is a step toward increased direct practical usability of IIASA's research results