| With the development of computer technology,a new form of office occur,office automatic.Compiling of the curriculum is one of the most important,complicated work in high school management.High school timetabling combined with characteristics of Mutile-objective,huge numbers of students,mass data,limited teaching resource.Clearly,there is a lot of drawback in previous manual timetabling.It is inefficiency and hard to suit the requirements.Because of it’s time and human resource consumption.In addition,manual timetabling is also not convenient to change curriculum schedule once the teachers or classroom are last-minute change.Conflicts can appear between classroom and selective course of students.Making full use of powerful computation ability of computer and software development has become a hot topic in high school timetabling problem.Timetabling problem was proved to belong to NP-complete class in early 1970 s,and was a combination optimization problem that restricted by multi-object.Genetic Algorithm is a computational model which imitate the natural selection of Darwinism’s Evolutionism and evolutionary processes of Genetic theory.Genetic algorithm is a approaches that imitated evolutionary processes to find global optimum solution.It used to solve complicate or nonlinear problem that traditional search methods can not sort.Genetic algorithm can solve the NP-hard combined problem efficiently.In this paper,the main works are fellows:(1)Discusses the restrict condition,influence factor,objective optimization and uncertainty of timetabling problem in detail.(2)Description of mathematical model of the timetabling problem and construct a model of timetabling problem according to my school data.(3)Introduce several timetabling algorithms and study the improvement of basic Genetic Algorithm,I put forward a new Adaptive Genetic Algorithm and apply it to the timetabling.(4)Using computer simulation and testing of ocourse scheduling base on Improvement Adaptive Genetic Algorithm,then analyse the outcome of the experiments.The results of comparing our algorithm with Genetic Algorithm,Adapative Genetic Algorithm Greedy Algprithm show that Improvment Adaptive Genetic Algorithm has better convergence. |
