Research On Timetable And Auto-generating Test Paper In College Based On Hybrid Intelligent Algorithm

This paper mainly discusses the research on the problems of the timetable and auto-generating test paper in university management by using the mixed intelligent algorithm. The paper summarizes the structure, the function and the characteristics of the genetic algorithms and the simulated annealing algorithm, and also analyzes the main characteristics and present situation of the chaos theory. In view of the sole intelligent algorithm existing problems and insufficiency, the author designs three kinds of mixed intelligences algorithm: the Chaos Genetic Algorithms, Heredity Annealing Algorithm, Heredity Simulation Annealing Algorithm. And the paper has conducted more thorough research by using the mixed intelligent algorithm to the university class schedule application, the test paper grouping and the test time arrangement. The paper's main research field is as follows:The paper analyzes the principle of scientific, reasonably arranging the class schedule problem. It introduces the chaos to the genetic algorithms, using the chaos switch genetic algorithms could fully use the chaos sequence intrinsic regularity, effectively guiding the overlapping and the variation operation; But after joining the chaos search strategy in the genetic algorithms, it has improved the algorithm search space greatly, at the same time avoiding the standard genetic algorithms being easy to fall into the partial minimum flaw. On basis of the intelligent optimizations algorithm, it has carried on the solution experiment to the class schedule problem, and analyzed and compared the different algorithm and different parameter obtaining test result.In the analysis of stochastic selection law and the recollection trial method group function test systematic insufficiency and in the shortcoming foundation, the paper proposes a new method of versatile automatic algorithm. The algorithm core is to apply the group volume system to the matrix theory method to establish the mathematical model in which the multi-objectives optimize, use the weight coefficient method to transform the multi-objectives to the simple target. It has solved the problem which many goals conflicts mutually, and has carried on the detailed discussion to each constraint condition of the mathematical model. In the genetic algorithms introduction simulated annealing algorithm, will design the mixed algorithm to the question of volume system solutions.