This paper discusses various types of constraints, difficulties and solutions to overcome the challenges regarding university course allocation problem. A hybrid evolutionary algorithm has been defined combining Local Repair Algorithm and Modified Genetic Algorithm to generate the best course assignment. After analyzing the collected dataset, all the necessary constraints were formulated. These constraints manage to cover the aspects needed to be kept in mind while preparing clash free and efficient class schedules for every faculty member. The goal is to generate an optimized solution which will fulfill those constraints while maintaining time efficiency and also reduce the workload of handling this task manually. The proposed algorithm was compared with some base level optimization algorithms to show the better efficiency in terms of accuracy and time.
翻译:本文件讨论了各类制约因素、困难和克服大学课程分配问题挑战的解决方案。混合进化算法已经界定,结合了当地修复算法和改良基因算法,以产生最佳课程分配。在分析所收集的数据集后,已制定了所有必要的制约因素。这些制约因素设法涵盖了需要铭记的各个方面,同时为每个教职员准备自由而高效的课级安排。目的是产生一种最佳解决办法,既能满足这些制约因素,又能保持时间效率,并减少人工处理这项任务的工作量。拟议的算法与一些基础水平优化算法进行了比较,以显示在准确性和时间方面的效率。