Towards an intelligent repository of scheduling methods

Scheduling is still poorly understood and applied in industry, often leading to unsatisfactory results. The provision of an intelligent repository of scheduling methods (SMs), aiding industrial users in selecting appropriate SMs would be most beneficial. It would also help bridge the gap between academic researchers and industry, by providing a common framework for the definition of scheduling needs and indicating to what degree existing SMs reply to them. We present a new expert system, called SMCT (scheduling method choice tool), that performs this function. We concentrate on two of its aspects: 1) concerning communicating with users who are not experienced in scheduling problems and terminology; 2) and concerning a novel way of structuring scheduling knowledge that is adapted to industrial and academic users