Abstract:
Nowadays, scheduling problems such as
employee scheduling, university timetabling,
arise in almost all areas of human activity. In the
literature, there are many methods to solve it.
Some of the most effective techniques on the
benchmark data in the literature are Meta
heuristic. However, these methods depend upon
parameter tuning or the way of embedding
domain knowledge .As a result, they are not
capable of dealing with other different problems
.Therefore, this has led to the development of
hyper heuristics system. In this paper, we
propose the extended great deluge (EGD)
method as a move acceptance method to drive
the selection of low level heuristic within hyper
heuristic framework. It is applied to a benchmark
set of examination timetabling problem as an
instance of a constraint based real world
optimization problem.
