Courses arrangement algorithm

Abstract

The invention relates to a courses arrangement algorithm. The algorithm includes establishing a time arranging model and a classrooms arranging algorithm. The time arranging model comprises constraint conditions and an objective function, and then branch-bound algorithm is adopted to solve the time arranging model to achieve a group of solutions, the group of solutions is D time arranging results; the classroom arranging algorithm is proceeded aiming at the D time arranging results, and finally output of the classroom arranging results related to the time arranging results is a courses timetable. By the application of the courses arrangement algorithm, time is arranged before classrooms are arranged, the courses arranging is not only simple, but also high effective, and thereby the courses arrangement algorithm is more widespread. What's more important is that the courses arrangement algorithm also defines a plurality of flexible regulations, by the setting of the flexible regulations, special requirements to the courses timetables of more colleges and universities are met, and the courses arrangement algorithm is more diverse and easy to popularize.

Description

technical field [0001] The invention relates to the technical field of electronic information, in particular to a class scheduling algorithm. Background technique [0002] With the merger and expansion of colleges and universities, class scheduling is an extremely heavy and very important task in college teaching management, and it is the premise and basis for ensuring the normal teaching order. Today, with the expansion of enrollment in colleges and universities, the shortage of teaching resources and the diversification of school-running forms, it is not easy to obtain a reasonable timetable. [0003] Class scheduling problem is a typical combinatorial optimization problem, which has been proved to be NP-complete. [0004] Most of the earliest class scheduling was done manually. Due to the cumbersome work and huge workload, there were more problems when scheduling courses in larger universities. [0005] Most of the existing solutions to the problem of course scheduling ...

AI Technical Summary

Problems solved by technology

The genetic algorithm is applied to the problem of scheduling courses, which is to gradually approach the set goal. First, the courses are arranged in the schedule according to the initial conditions. Class space consumption is large, especially after randomly generating a lot of timetables and checking according to the conditions, those that do not meet the conditions are discarded, and the remaining ones are randomly modified by imitating genetics to form many new sub-timetables, and those that do not meet the conditions are abandoned until the task is completed; other Simulating natural selection and genetics, that is, survival of the fittest and survival of the fittest, does not actively generate curriculum according to conditions, and there is a certain degree of blindness, which will inevitably lead to a lot of waste of time

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