The paper presents selected issues related to design and implementation of model based Decision Support Systems (DSS). For over ten years the SDS Program has been involved in cooperation with various projects at IIASA and in collaborating research institutes. This cooperation has resulted in the development of many DSS, which in turn stimulated research on the theory and methodology of decision...

This article has been developed in the frame of an IST European Project, where Companies and Universities of several countries of Europe have collaborated. The work presents a Decision Support System (DSS) to provide help in the bidding process. Critical decisions as bid/no bid, make/buy or decision of best final proposal have been realised. The tool performs a risk analysis and it uses the res...

This paper presents the process and impact of the application of a group decision support system (GDSS) in the reform of post-Bologna graduate and postgraduate study programmes in two higher education institutions in Slovenia. Four experiments with four groups including both students and staff were performed. We have used the GDSS tool TeamWorks to organize, moderate and document meetings inten...

Production scheduling is an important decision-making process that has embraced technology as computers and information systems became cheaper and easier to use. The history of production scheduling is not one of replacing human decision-makers with algorithms, however. This paper provides a historical perspective on the decision support tools that have been developed to improve production sche...

Whole genome sequencing (WGS) is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic info...

The research described in this paper addresses issues of designing a computationally effective decision support system which can assist a decision maker in making an optimal choice between several discrete alternatives. A new hybrid approach to multi-attribute decision making under uncertainty incorporating Neural Networks and the Dempster-Shafer theory of evidence is introduced. A neural netwo...

As a typical phenomenon of eutrophication pollution, algal bloom threatens public health and water security. The governance of algal bloom is largely affected by administrators’ knowledge and experience, which may lead to a subjective and one-sided decision-making result. Meanwhile, experts in the specific field can provide professional support. How to utilize expert resources adequately and au...

The healthcare industry collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Clinical Decision support systems (CDSS) can now use advanced technologies such as On-Line Analytical Processing (OLAP) and Data Mining to deliver advanced capabilities. This paper presents a prototype CDSS using OLAP with Data Mining (OLAP Mining) wh...

Design engineers working in the automotive industry have to take many design decisions, based on numerous diverse criteria. This results in a high workload of complex decisions. One way to reduce decision complexity and improve decisions could be to improve design tools. Decision support systems (DSSs) have been used in a managerial context to improve decisions. In this article, the authors ass...

We propose a novel approach to the well-studied problem of making a finite, ordered sequence of decisions under uncertainty. Most existing work in this area concentrates on graphical representations of decision problems, and requires a complete specification of the problem. Our approach is based on a formal logic, such that the choice of an optimal decision can be treated as a problem of logica...