[计算机科学] 大学师生关系的变邻域搜索 指派问题 [推广有奖]

摘要翻译：
本文研究了局部搜索启发式方法，特别是变邻域搜索方法，以解决高校实际工作中的一个指派问题。在这里，学生必须被分配到由教职员工提议和支持的科学主题。这个问题涉及到学生在一定的偏好下的优化问题，这种偏好可能会在申请某一主题时表现出来。可以观察到，对于测试的问题实例，可变邻域搜索导致了更好的结果。一个实例取自实际案例，而其他实例则是基于真实世界的数据生成的，以支持更深入的分析。通过整合第二个目标函数，同时平衡工作人员的工作量，同时最大限度地提高学生的效用，这是问题的一个扩展。该算法已在计算机系统中原型实现。这方面的一个重要方面是将研究工作应用于其他科学机构的问题，从而提供决策支持功能。
---
英文标题：
《Variable Neighborhood Search for the University Lecturer-Student
  Assignment Problem》
---
作者：
Martin Josef Geiger, Wolf Wenger
---
最新提交年份：
2008
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  The paper presents a study of local search heuristics in general and variable neighborhood search in particular for the resolution of an assignment problem studied in the practical work of universities. Here, students have to be assigned to scientific topics which are proposed and supported by members of staff. The problem involves the optimization under given preferences of students which may be expressed when applying for certain topics.   It is possible to observe that variable neighborhood search leads to superior results for the tested problem instances. One instance is taken from an actual case, while others have been generated based on the real world data to support the analysis with a deeper analysis.   An extension of the problem has been formulated by integrating a second objective function that simultaneously balances the workload of the members of staff while maximizing utility of the students. The algorithmic approach has been prototypically implemented in a computer system. One important aspect in this context is the application of the research work to problems of other scientific institutions, and therefore the provision of decision support functionalities.
---
PDF链接：
https://arxiv.org/pdf/0809.1077