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An effective constraint-aware optimization method for university course timetabling problem

机译:大学课程时间表问题的一种有效的约束感知优化方法

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University course timetabling is known to be hard combinatorial optimization problem. It is difficult to tackle the constraints including the classroom, course and the teacher requirement. Some optimization approaches have been proposed in order to solve this kind of problem, one of the efficient solution methods for this problem is tabu search. But these methods little take attention to the constraint relationships, mainly concern the conflict circumstances. In this paper, constraint-aware modeling method is proposed based on the fuzzy Petri net, which can respect the constraint relationships among the courses, the classrooms and the teachers. Then we locate the best legal firing sequences in the constraint model by the differential evolution (DE) method, in order to obtain the optimal course timetabling plan. The theoretical analysis and specific example show that the method is very effective.
机译:众所周知,大学课程的时间表安排是很难的组合优化问题。解决包括教室,课程和教师要求在内的各种限制非常困难。为了解决这种问题,已经提出了一些优化方法,针对该问题的一种有效的解决方法是禁忌搜索。但是这些方法很少关注约束关系,主要关注冲突情况。本文提出了一种基于模糊Petri网的约束感知建模方法,该模型可以考虑课程,教室和教师之间的约束关系。然后,通过差分进化(DE)方法在约束模型中找到最佳的合法解雇顺序,以获得最优的课程时间表。理论分析和具体算例表明,该方法是有效的。

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