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：本文探讨了大学课程分配问题中涉及的各种约束条件、难点及应对挑战的解决方案。通过结合局部修复算法与改进遗传算法，定义了一种混合式进化算法以生成最优课程分配方案。在分析收集的数据集后，对所有必要约束条件进行了公式化表述。这些约束条件涵盖了为每位教师编制无冲突且高效的课程表时需要考量的各项要素。研究目标是生成满足这些约束条件的优化解，同时保持时间效率，并减少人工处理此项任务的工作量。将所提算法与若干基础优化算法进行比较，结果表明其在准确性和时间效率方面具有更优性能。