多校区高校自动排课系统的研究与设计

发布时间：2018-01-13 21:33

本文关键词：多校区高校自动排课系统的研究与设计　出处：《电子科技大学》2013年硕士论文　论文类型：学位论文

【摘要】：科学、规范的教学管理是获得高水平教学质量的必要条件，课表安排则是教学管理中最为关键的一环。制定一个灵活、高效、人性化的课程表，将对后继教学活动的有序开展起到至关重要的作用。因此，对课表安排问题进行深入、细致的研究，具有非常重要的现实意义。近几年，很多高校因为扩招而使得教学资源变得越来越紧张，在此背景之下，以往用人工安排课表的方法因为过程复杂、耗时长、准确度无法保证等不足而不能满足现代教学要求。另外，随着计算机的普及，其快速、准确、自动化的优点给各个行业带来了很大的便利。因此，可以将计算机运用于现代教学活动，根据教学要求，利用计算机求解不同课程间的排列组合，从而得出相应的排课方案。排课实质上是为了实现对有限教学资源的合理分配，优化教学质量，实现教学目标而采取的规划，即安排适当的教室、教师在恰当的时间完成全部的教学任务。排课问题具有以下几个特点：具有一定约束条件、非线性以及多目标优化。而对于这种比较难解决的非线性方面的命题，遗传算法具有很大优势。其原理是利用生物遗传规律，运用群体搜索的理论，，有效弥补了以往搜索方法的不足。本文对多校区排课中出现的问题、原因进行了研究。分析了多校区排课中的影响因素、主要约束条件、求解目标和难点，并根据多校区排课问题的特点，将6元组问题简化成2元组问题，缩小问题规模，完整阐述了多校区排课的数学模型。论文在遗传算法的相关理论基础上，讨论了利用遗传算法解决排课问题的可能，并据此提出了相应的解决算法。对算法从编码、交叉、变异设计进行改进：设计了二维资源片十进制编码方案，既方便初始种群产生和冲突检测，又减小了时间复杂度；提出了一套新的能有效解决多校区排课的方法。同时，该算法充分考虑了排课时涉及到的一些重要因素，对其间发生的冲突提出了相应的解决方法。最后，通过对吉林工商学院多校区教学现状的分析，实现了基于改进遗传算法的课表编排系统，并将该系统应用于实际排课过程，经理论和实践表明该系统具有良好的自适应性，且效率较高。
[Abstract]:Scientific and standardized teaching management is the necessary condition to obtain the high level teaching quality, and the schedule arrangement is the most important link in the teaching management. Make a flexible, efficient and humanized curriculum. It will play a vital role in the orderly development of subsequent teaching activities. Therefore, it is of great practical significance to make a thorough and detailed study on the arrangement of curriculum in recent years. Many colleges and universities because of the expansion of teaching resources become more and more tight, in this context, in the past, the use of manual scheduling method because of the complexity of the process, time-consuming. Accuracy can not be guaranteed and can not meet the requirements of modern teaching. In addition, with the popularity of computers, its advantages of speed, accuracy and automation have brought great convenience to various industries. The computer can be used in modern teaching activities. According to the teaching requirements, the computer can be used to solve the arrangement and combination of different courses. In essence, it is to achieve the reasonable allocation of limited teaching resources, optimize the quality of teaching, achieve the goal of teaching planning, that is, arrange appropriate classrooms. The teacher completed all the teaching tasks at the right time. The course scheduling problem has the following characteristics: some constraints, nonlinearity and multi-objective optimization, but for this difficult to solve the nonlinear aspects of the proposition. Genetic algorithm (GA) has great advantages. Its principle is to make up for the deficiency of previous search methods by using biological genetic law and the theory of population search. This paper studies the problems and causes in multi-campus scheduling, analyzes the influencing factors, main constraints, solving objectives and difficulties in multi-campus scheduling, and according to the characteristics of multi-campus scheduling problems. The 6-tuple problem is simplified into a 2-tuple problem, the scale of the problem is reduced, and the mathematical model of course scheduling in multi-campus is completely expounded. Based on the theory of genetic algorithm, this paper discusses the possibility of using genetic algorithm to solve the problem of course scheduling, and puts forward the corresponding algorithm. The mutation design is improved: a 2-D resource slice decimal coding scheme is designed, which not only facilitates the initial population generation and conflict detection, but also reduces the time complexity; A new method to solve the problem of multi-campus scheduling is proposed. At the same time, some important factors involved in the course scheduling are fully considered, and the corresponding solutions to the conflicts between them are put forward. Finally, through the analysis of the current teaching situation of Jilin Polytechnic College, the course schedule arrangement system based on improved genetic algorithm is realized, and the system is applied to the actual course scheduling process. The theory and practice show that the system has good adaptability and high efficiency.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：G647;TP301.6

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