Abstract
The general timetabling problem is an assignment of activities to fixed time intervals, adhering to a predefined set of resource availabilities. Timetabling problems are difficult to solve and can be extremely time-consuming without some computer assistance. In this paper the application of constraint-based reasoning to timetable generation is examined. Specifically, we consider how a timetabling problem can be represented as a Constraint Satisfaction Problem (CSP), and propose an algorithm for its solution which improves upon the basic idea of back tracking. Normally, when a backtracking routine fails to find a solution, there is nothing of value returned to the user; however, our algorithm extends this process by iteratively adding constraints to the CSP representation. A generalized random model of timetabling problems is proposed. This model creates a diverse range of problem instances, which are used to verify our search algorithm and identify the characteristics of difficult timetabling problems.
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Banks, D., van Beek, P., Meisels, A. (1998). A heuristic incremental modeling approach to course timetabling. In: Mercer, R.E., Neufeld, E. (eds) Advances in Artificial Intelligence. Canadian AI 1998. Lecture Notes in Computer Science, vol 1418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64575-6_37
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DOI: https://doi.org/10.1007/3-540-64575-6_37
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