Every year or term each individual department of organization has to design a new timetable for subjects. The Class Timetable scheduling problem deals with the assignment of classes to a limited set of resources such as rooms, timeslots, set of lecturers and group of students in such a way to satisfy predefined constraints. All hard constraints must be satisfied, to obtaining a feasible solution. This problem is in class of NP-hard problem and is very difficult to solve by classic algorithm. Therefore optimizations techniques are used to solve them and produce optimal or almost optimal feasible solution instead of exact solution. In this paper we present a discussion of the research on class timetable scheduling and to solve this problem two algorithms i.e. Genetic Algorithm (GA) and Tabu search algorithm can be used. Because GA has ability to handle a very complex search space with high probability of success in finding the optimal solution and Tabu search is used its memorized ability to prevent from searching previous visited area, therefore it is easier to obtain optimal solution in a short time. Here we introducing modified approaches which do not allow violations of any hard constraints, and it produce only feasible solutions. For the departmental class timetable fitness value is evaluated by solving room wise timetable and according to that reaming class wise, lab wise and faculty load wise time table is being sorted. Therefore the aim of the research is to produce a good quality timetable. This gains us to get better solutions in a comparative short time.