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Add Mutation
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Swap: In this approach, you randomly select two slots in the week and swap their subjects.
This approach can help create more diversity in the population and can help the algorithm converge to a better solution.
Replace: In this approach, you randomly select a slot in the week and replace its subject with a new subject that is not already
present in that day or in the same time slot in other days. This can help introduce new subjects to the timetable and prevent
the algorithm from getting stuck in a local minimum.
Shift: In this approach, you randomly select a slot in the week and shift its subject to another slot in the same day or
in another day. This can help optimize the timetable by moving subjects to more appropriate slots or days.
Swap-Day: In this approach, you randomly select two days in the week and swap their subjects.
This can help introduce more diversity in the population and can help the algorithm converge to a better solution.
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Add more fitness functions
- Subject taught today then not tommorow
- Continuity of subjects will be appreciated
- Each day should have 5 slots filled only at max
- Load distribution check on students
- load distribution check on faculty
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Optimize repairing
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