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Lecture Schedule on Accounting Computer Department of Indonesia Computer University Using Genetic Algorithm

机译：遗传算法课程计算机大学会计计算机部讲学时间表

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The aim of this research is to obtain the best combination of scheduling of courses and lecturers but does not violate the constraints of the Accounting Computer Department of Indonesia Computer University. Hence, the need considered various aspects that affect scheduling of courses. From the aspect of lecturers, we need to consider to the possibility of the lecturer in question cannot be taught because the other academic activities, lecturer teaching more than one subject on the same day and same hour and lecturers already has a schedule of teaching in the Department of another. These problems included in the NP-Hard Problem (Nondeterministic Polynomial time), namely the entire alternative combinations should be tested. This research uses genetic algorithms approach specifically computational approach is to solve a problem that is modeled with the biological processes of evolution. Genetic algorithm will represent the solutions using genetic operations such as crossover and mutation. The result of this genetic algorithm shows the best fitness value one, which means there is no breach of a hard constraint. The best combination with making no use of high-frequency space and no lecturer teaching the high frequency.
机译：本研究的目的是获得课程和讲师的安排最佳组合，但并未违反印度尼西亚计算机大学会计计算机部门的制约因素。因此，需要考虑影响课程调度的各个方面。从讲师的方面，我们需要考虑讲师的可能性，因为其他学术活动，讲师教授多个主题的同一天和同一个小时和讲师已经有一个教学时间表部门的部门。这些问题包括在NP - 硬质问题（非确定性多项式时间）中，即应该测试整个替代组合。该研究使用遗传算法方法，具体计算方法是解决与进化生物过程建模的问题。遗传算法将使用诸如交叉和突变的遗传操作来代表解决方案。这种遗传算法的结果显示了最佳的健身值，这意味着没有违反艰难约束。最好的结合不使用高频空间，没有讲师教授高频。

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