Smart University Scheduling Using Genetic Algorithms

Omar Alhuniti, Rawan Ghnemat, M. El-Seoud
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引用次数: 0

Abstract

The purpose of this research is to apply genetic algorithm to solve University timetable scheduling problem which almost takes a long time Up to weeks of discussion and frequent changes and in the end it contains some errors and conflicts and lack of utilization of available resources as required, leading to additional costs and may lead to not note that existing human resources are not to mind equitable distribution, which ultimately leads to the low level of overall performance also we apply genetic Algorithm to get University timetable optimizing the use of resources and increase the popularity and reduce the number of his opponents. Definitely, we improve the genetic Algorithm to be more flexible to get the best result through making smart mutations depend on the gene fitness and compute fitness function value including all variables of timetable (instructors, halls, period of time and courses).
基于遗传算法的智能大学调度
本研究的目的是应用遗传算法解决大学课程表调度问题,这几乎需要很长时间,长达数周的讨论和频繁的变化,最终它包含一些错误和冲突,缺乏对可用资源的利用,导致额外的成本,并可能导致没有注意到现有的人力资源不考虑公平分配。并应用遗传算法得到大学时间表,优化资源利用,提高人气,减少对手数量。当然,我们改进了遗传算法,使其更加灵活,通过基于基因适应度的智能突变来获得最佳结果,并计算包含时间表(教员、厅堂、时间段和课程)所有变量的适应度函数值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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