Research And Application Of Timetable Problem Based On Genetic Algorithm

Timetable problem is one of the very important and complicated work in school teaching management. With the development of the college education, the number of students increasing continuously, it becomes a heavier task to arrange courses under the condition of limited classroom resource. Meanwhile, course arrangement has also become a key factor in teaching management, which to some extent has some influences on student training and the improvement of teaching quality.This thesis applies Genetic Algorithm and multi-objective optimization theory to the resolution of timetable problems, and proposes the random production and optimization algorithm of timetable schedule, which can to a large extent reflect the actual timetable situation as well as tries to obtain multi-objective optimization. The main task of this thesis includes:①A detail discussion of the influential factors and main restraining conditions in timetable problem. An analysis of resolution difficulties and objects in timetable problem .A description of timetable problem with mathematical model and an overall plan and technical line for the resolution of timetable problems.②Aiming at timetable problems, designing the gene coding scheme, chromosome structure and genetic operator, proposing the resolution to individual fitness evalution function.③With JSP as the foreground development tool and MYSQL as the background database, designing and implementing the automatic timetable system based on Genetic Algorithm.④Employing the above timetable optimization algorithm based on Genetic Algorithm to resolve the problems and carrying out following analysis of some intermediate parameters to testify the feasibility of the algorithm from the view of experiment.This thesis focuses on the influences of timetable Genetic Algorithm on the efficiency of the timetable system. It is found based on the research that the complexity of the algorithm can be largely reduced and the search efficiency of timetable system considerably enhanced, by building the mixed gene coding, improving hybrid way and quantifying the weighted parameters according to the teacher's perferenced schedule. It can be seen from the experimental results that the going after objective value indicates that the algorithm is stable and optimal, so the solution is satisfied.