Navigation:  Modules > Course Scheduling > Course scheduling > Course optimisation > Partial optimisation > Partial optimisation

If no entries are likely to hinder optimisation , the corresponding subset optimisation window will open make make or prohibit course-cluster assignments and where you can start the actual optimisation run.

 

In the right section of the top window area - the status display - data about the solutions that have been found is displayed during and after optimisation. After optimisation the <OK> button serves to save the result of optimisation or any manual entries. Clicking the <Cancel> button discards the results found so far and takes you back to the 'Definition of the subsets' dialogue.

 

 

 

The middle part of the window contains a simplified cluster-course-matrix with the courses of the subset and the clusters to be filled by partial optimisation. The 'Students' column displays the number of students attending the relevant course as well as the minimum and maximum number of students entered for this course (in parentheses). Red indicates that the maximum number of students has been exceeded and green that the minimum number has not been reached.

 

The students of the selected course are listed individually and details about possible clashes are given in the bottom section of the window. You can see the number of students as well as details about eventual clashes for the selected cluster.

 

If you have added clusters to the subset, the courses of the clusters which already have been entered are in the middle section (marked with an 'X') and are also locked. This ensures that existing cluster definitions are retained.

 

You can also manually assign courses to certain clusters and lock clusters for certain courses. In addition, you are provided with information on how well the selected would fit in with a particular cluster.

 

 

 

How long optimisation takes mostly depends on the following factors:

 

 

 You can start with simple optimisation for the initial optimisation run. If no solution is found, try extended optimisation.

 

All possible combinations of clusters are generally tested. The algorithm tries to recognise identical solutions in order to save time and to forego the needless examination of combinations :

 

A solution is equal if clusters are only swapped (e.g. cluster 1 instead of 3).

 

Parallel courses (e.g. E1 , E2 , E3 ) are seen as equal if they are always selected together in every student choice..

 

 

Note: Blocked, locked courses/clusters

If you lock clusters or exclude courses from certain clusters, different clusters and courses are no longer equal and therefore the number of combinations which has to be examined can be drastically increased (a hundredfold or even more).

 

 

The number of student clashes as well as the number of the over- and underbooked courses are shown for the best and for the last solution. The course-cluster-matrix shows the interim results of cluster allocation.

 

You can examine the best solutions after optimisation. Select the solution you are interested in from the list-box The number of clashes as well as the number of overbooked and underbooked courses are indicated in parentheses next to number of the solution.

 

 

Note: Unrealistic numbers

If the minimum and maximum numbers of students for a course are not realistic (based on their course choices), Untis calculates the optimum number of students for the course in question, and the number of over- or booked courses is determined on the basis of this number. This can result in differences to the display in the course-cluster-matrix.

 

If, for example, a course can be taken by at least 5 and at most 25 students (according to the entry in the course-students-overview), but only 3 students have chosen this course as an alternative, then these 3 students are the most that can be assigned to the course after optimisation. This course would then be marked as underbooked in the course-cluster-matrix whereas it would not be counted as underbooked in the solution display.