Design anf development of an Examination office management system

Description

Abstract Scheduling course, examination, invigilation timetables for a large array of courses is a very complex problem which often has to be solved manually by the examination office staff even though results are not always fully optimal. Timetabling being a highly constrained combinatorial problem, this work attempts to put into play the effectiveness of evolutionary techniques based on Darwin’s theories to make sure scheduled timetables do not violate fundamental constraints. Genetic Algorithm is a popular meta-heuristic that has been successfully applied to many hard combinatorial optimization problems which includes timetabling and scheduling problems. In this work, the course sets, venues and time allocations are represented by a multidimensional array on which a local search is performed and a combination of the direct representation of the timetable with heuristic crossover is made to ensure that fundamental constraints are not violated.