A Survey of Automated Timetabling
Artificial Intelligence Review
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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Motivation -- To take steps towards identifying how the number of explicit external constraints may affect performance in a constraint satisfaction task, here timetabling design. Research approach -- Thirty-seven psychology students, with no/little formal design training took part in a computer-based experiment wherein they completed three timetabling designs. Tasks varied in the number of external constraints implemented by varying the number of rules applicable to each task. Performance measures included number of successful class placements, task completion times and number of constraint violations during problem solving. Findings -- The results suggest that having a greater number of rules/constraints is associated with poorer design performance. Originality/Value -- The research provides some initial quantitative evidence in an area of design problem solving, specifically constraint satisfaction, in which there is a shortage of human-centred research. Take away message -- Increasing the number of external constraints reduces design performance.