Any problem has a set of valid results. It is said to form the solution space. In an
optimization problem, the main aim or goal is to find results that maximize or
minimize a set of criteria. If we look at the solution space as an
n-dimensional space then essentially we are searching for a global minima or
maxima in the solution space. The Genetic Algorithm is a type of algorithm for
searching the solution space and finding maxima or minima, though not
necessarily the global maxima or minima. Timetable scheduling is always said to
be a complex optimization problem which has shown to be related to the clique
of minimization problem which is called NP complete. In such kind of problem
where no efficient algorithm is known, it is ideal to apply genetic algorithm
to such kind which is used for search a solution space. It is necessary to
realize that such scheduling is a world problem that has an immediate
application in various forms of timetabling including, examinations, public
transport and roaster, though in no way limited to.
Scheduling is one of the important tasks that we encountered in our daily life situations.
There are various types of scheduling problems which includes personnel
scheduling, production scheduling, and educational timetable scheduling etc.In
educational timetable scheduling, there are many constraints that need to be
satisfied in order to get a clear solution which has made it a very hard task.
Educational timetable scheduling can be called a non-polynomial hard (NP hard)
which means that, there are no exact algorithms that can solve this problem of timetable
scheduling. Hence, evolutionary techniques have been used to solve the time
table scheduling problem.
