Design and Implementation of Model-based Decision Support Systems Design and Implementation of Model-based Decision Support Systems

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 speci c 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, di erent 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 arti cial neural nets to decision support are also presented.