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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/3894 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/3894 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/3894 archive 351 disk0/00/00/41/25 2016-01-15 02:04:12 2021-08-27 17:14:49 2016-01-15 02:04:12 monograph show 2 Makowski M. 1254 0000-0002-6107-0972 pub iis_cmp iis_met iis_sys prog_mda Decision making often requires the analysis of large amount of data and complex relations. Computerized tools designed and implemented for such purposes are called Decision Support Systems (DSS). A DSS, which is typically a problem specific tool, usually helps in the evaluation of consequences of given decisions and may advise what decision would be the best for achieving a given set of goals. In such cases, an analysis of a mathematical model can support rational decision making. The paper provides an overview of the methodology of the design and deals with practical aspects related to implementations of model-based decision support systems. In particular, different approaches to the analysis of a model using simulation and optimization are summarized. Various optimization techniques are discussed in this context, including multi-criteria optimization used for a model analysis. The paper summarizes also problems of hardware selection and of software development. Modular software tools applicable to DSSs, including a tool for data interchange, are characterized. Selected issues of implementations of modular solvers and of applications of artificial neural nets to decision support are also presented. 1994-12 published WP-94-086 WP-94-086 10 193 public working_paper IIASA, Laxenburg, Austria 42 FALSE info:eu-repo/semantics/book