Class Timetable Scheduling with the help of AI

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In this paper we introduced a tool to resolve the timetable-scheduling problem with different constraints (hard and soft). This tool uses genetic algorithm to provide the optimal or near-optimal solution. Genetic Algorithm (GA) was widely used for timetabling but as many studies indicated the solution for timetabling is different from one institution to another because of the different types of institutions and different constraints within the same type. Most researchers were looking for the optimal solution to time tabling problem in respect of a set of constraints. This NP-Hard problem required heuristic methods among which GA solution. The problem is that GA may, in one side, runs into minima and, in the other side, the solution may not be the wanted solution, even if it has the best fitness, because some soft constraints were not satisfied. For this reason, our tool shows a number of solutions got from GA and then gives the possibility for the user to manipulate the timetable in a way to get the needed solution by recalculating the fitness to see if a constraint is broken each time a modification is done.

Genetic, Algorithm, AI, Java