Modified approach to optimize the University examination timetabling problem

The timetable is the problem of placing particular resources due to constraints in a limited number of times lots and space, in order to satisfy a set of goals that is used to a variety of problems. Among these problems, one can point out the University Examination Timetabling Problem (UETP), which is the particular importance in educational problems. The university examination timetabling problem defined as the assignment of a certain set of exams to a fixed number of time slots and rooms, so that it meets all the hard constraints, also soft constraints are optimized as much as possible. This research presents a modified approach to optimize the incapacitated UETP. In this approach, a proposed Genetic Algorithm (GA) is modified by local search operators. These operators will make alterations to the timetable. This involves shifting or changing scheduled exams and thus greatly improve the ability of the algorithm to search. The efficiency of the proposed approach is compared with other techniques from literature using the Carter’s benchmark. The computational results show that this approach is quite effective and competitive in improving the solutions and is able to produce better solutions in most of the datasets compared with other algorithms.