Year: 2000
Type: article
Abstract: Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied soft constraints, however, may be violated, but should be satisfied as much as possible. This paper shows how to model the timetabling problem as partial constraint satisfaction problem and gives a concise finite domain solver implemented with constraint handling rules that, by performing soft constraint propagation, allows for making soft constraints an active part of the problem-solving process. Furthermore, efficiency is improved by reusing parts of the timetable of the previous year. This prototype needs only a few minutes to create a timetable while manual timetabling usually takes a few days. This was presented at the Systems'98 Computer Fair in Munich and several universities have inquired about it.
Source: Applied Artificial Intelligence
Authors: Slim Abdennadher, Michael Marte
Institution: Ludwig-Maximilians-Universität München
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W1997697966