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Abstract
The typical tuition planning challenge that universities face is to optimize students’ and teachers’ timetables on a weekly basis. While crucial for operational arrangement of tuition, such short-term planning is often done in relative isolation from longer-term strategic considerations, such as organizational competence development. This article presents an heuristic method, based on genetic algorithms, for long-term strategic planning of tuition for multi-year university degree programmes, at the semester level. The proposed method attempts to produce such a tuition schedule that satisfies given pre-requisite knowledge constraints, while honouring teacher-specific preferences, such that the workload across the teachers is as uniform as possible. The proposed method accommodates many real-world constraints, and can be applied to several distinct student groups advancing in parallel. As an application, the proposed method is used for optimizing the tuition schedule of a mechanical engineering degree programme at a Finnish university.
Acknowledgements
The authors would like to thank the anonymous reviewer for constructive criticism and for suggestions that helped improve the paper.
Notes
No potential conflict of interest was reported by the authors.
1 A module, for example ‘System Design’, may consist of several different courses.
2 For example, students of ‘Marine Engineering’ and students of ‘Energy Technology’ constitute two distinct groups in the degree programme of ‘Mechanical Engineering’ at TUAS.
3 For example, Engineering Science is a common module while Ship Design is a module specific to the Marine Engineering student group, in the Mechanical Engineering degree programme at TUAS.