Smart University Scheduling Using Genetic Algorithms

The purpose of this research is to apply genetic algorithm to solve University timetable scheduling problem which almost takes a long time Up to weeks of discussion and frequent changes and in the end it contains some errors and conflicts and lack of utilization of available resources as required, leading to additional costs and may lead to not note that existing human resources are not to mind equitable distribution, which ultimately leads to the low level of overall performance also we apply genetic Algorithm to get University timetable optimizing the use of resources and increase the popularity and reduce the number of his opponents. Definitely, we improve the genetic Algorithm to be more flexible to get the best result through making smart mutations depend on the gene fitness and compute fitness function value including all variables of timetable (instructors, halls, period of time and courses).