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首页> 外文期刊>Journal of computational science >University course timetabling using hybridized artificial bee colony with hill climbing optimizer
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University course timetabling using hybridized artificial bee colony with hill climbing optimizer

机译:使用混合人工蜂群和爬坡优化器的大学课程时间表

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摘要

University course timetabling is concerned with assigning a set of courses to a set of rooms and timeslots according to a set of constraints. This problem has been tackled using metaheuristics techniques. Artificial bee colony (ABC) algorithm has been successfully used for tackling uncapaciated examination and course timetabling problems. In this paper, a novel hybrid ABC algorithm based on the integrated technique is proposed for tackling the university course timetabling problem. First of all, initial feasible solutions are generated using the combination of saturation degree (SD) and backtracking algorithm (BA). Secondly, a hill climbing optimizer is embedded within the employed bee operator to enhance the local exploitation ability of the original ABC algorithm while tackling the problem. Hill climbing iteratively navigates the search space of each population member in order to reach a local optima. The proposed hybrid ABC technique is evaluated using the dataset established by Socha including five small, five medium and one large problem instances. Empirical results on these problem instances validate the effectiveness and efficiency of the proposed algorithm. Our work also shows that a well-designed hybrid technique is a competitive alternative for addressing the university course timetabling problem.
机译:大学课程时间表与根据一组约束将一组课程分配给一组房间和时隙有关。使用元启发式技术已经解决了这个问题。人工蜂群(ABC)算法已成功用于解决能力丧失的考试和课程时间表问题。本文提出了一种基于集成技术的新型混合ABC算法,用于解决大学课程排课问题。首先,结合饱和度(SD)和回溯算法(BA)生成初始可行解。其次,在所雇用的蜜蜂运营商中嵌入了一个爬山优化器,以在解决该问题的同时增强原始ABC算法的本地开发能力。爬山迭代地导航每个人口成员的搜索空间,以达到局部最优。使用由Socha建立的数据集对提出的混合ABC技术进行评估,该数据集包括五个小,五个中等和一个大问题实例。这些问题实例的经验结果验证了所提算法的有效性和效率。我们的工作还表明,精心设计的混合技术是解决大学课程时间表问题的有竞争力的替代方法。

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