Design aspects of an advanced model-oriented DSS for scheduling problems in civil engineering

The paper gives some design features of the architecture of a DSS for scheduling problems under development as part of a long-term project and designated as prototype for a new kind of advanced support system with strong AI potential. Support is intended for people in applications, scientific users and students. Main features are a thorough multi-attribute decision modelling, the incorporation of robust methods for stochastic models and the full incorporation of an enormous body of available algorithmic tools in the field. Other aspects are a number of features for a self-adaptive behaviour, several knowledge-based components and the availability of an Eigen-model of the system. In addition, the architecture also allows a ‘genetic’ adaptation cycle. The system will have components for explaining its own functioning, it is designed to document considerable parts of the user scientific knowledge in the area and will make parts of this algorithmic or modelling knowledge available via Computer Aided Instruction devices.