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Course optimisation |
  
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Course optimisation |
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The two main tasks of course scheduling are to define course clusters, i.e. determine which courses should best be taught at the same time, and to allocate students to actual courses when several alternative courses are specified in their course choices.
Several constraints must be taken into account:
| • | No teacher may teach two different courses within the same cluster . |
| • | No student should take two different courses within the same cluster , otherwise choices must be redefined |
| • | Clusters should formed in such a way that as many students as possible take a course in this cluster. |
| • | Students should be allocated to parallel courses as evenly as possible, e.g. course bio1 should not be taken by 40 students when the parallel course, bio2, is only taken by 10 students. At the same time, alternative courses requested with a higher priority by students should be given preferential treatment during assignment. |
| • | A number of user parameters must also be observed (e.g. minimum and maximum number of students per course, student optimisation codes, and cluster conditions). |
The course scheduling module provides tow different optimisation methods for this purpose: standard optimisation and partial optimisation (also called part optimisation).
Standard optimisation
The advantage of standard optimisation is its ease of use. After defining the constraints you only have to launch optimisation, and Untis will attempt to find a complete solution while keeping to the conditions as closely as possible.
Partial optimisation
In contrast, partial optimisation only deals with a part of the courses which have to be scheduled, but still examines the entire mathematical solution space. Partial optimisation usually yields better results than standard optimisation, but its use requires a certain level of experience from the user.
In practice, it is generally advisable to use a combination of both methods together with some manual scheduling with the aid of the course-cluster-matrix .
Example
For example, taking an ethics or religious knowledge lesson may be compulsory or students of a particular class level/year may have to take one of the three English courses on offer. Your specialist knowledge of these matters must underpin your scheduling activities. In many cases manually scheduling these courses in a clusters (and then fixing the cluster) will speed up subsequent optimisation significantly and greatly improve the quality of the solutions.