Partial Neighborhood Search for the Post-Enrollment Course Timetabling Problem
Partial Neighborhood Search for the Post-Enrollment Course Timetabling Problem
复制标题
针对注册后课程时间表问题的部分邻域搜索
DOI：
10.1016/j.cor.2017.09.014
复制
发表时间：
2018
影响因子：
4.6
通讯作者：
Yuicih Nagata
中科院分区：
文献类型：
--
作者：
Nagata Yuichi;Imamiya Akinori;Ono Norihiko;31.沖 展彰，小野 典彦，永田 裕一;Yuichi Nagata;Yuicih Nagata
在这项研究中，我们提出了一个基于局部搜索的算法后注册为基础的课程编排问题，它采用了一种机制，在搜索过程中的邻域大小进行调整。在每次迭代中，只需通过构造一个随机部分邻域来改变邻域大小，该随机部分邻域被定义为整个邻域的随机子集。使用随机部分邻域的主要原因是为了控制搜索过程中探索和利用之间的权衡，并考虑了两种更新策略来改变邻域大小。所提出的算法进行了测试，使用著名的基准集，并获得的结果是高度竞争力与这些基准集开发的领先的求解器。
In this study, we present a local search-based algorithm for the post-enrollment-based course timetabling problem, which incorporates a mechanism for adapting the neighborhood size during the course of the search. At each iteration, the neighborhood size is changed simply by constructing a random partial neighborhood, which is defined as a random subset of the entire neighborhood. The main reason for using a random partial neighborhood is to control the trade-off between exploration and exploitation during search, and two updating strategies are considered for changing the neighborhood size. The proposed algorithms were tested using well-known benchmark sets and the results obtained were highly competitive with those produced by the leading solvers developed for these benchmark sets.