{"title":"Student assignments with preferences and maximum diversity","authors":"Arne Schulz","doi":"10.1007/s10479-026-07189-8","DOIUrl":null,"url":null,"abstract":"<div><p>The paper considers the assignment of students to seminars regarding three hierarchical objectives: maximizing the students’ preferences, maximizing the within seminar diversity, minimizing the between seminar diversity variation. While the first objective pictures the students, preferences, the second and third picture the school’s preference of having comparable seminar groups. To reach this aim the paper extends the well-known Maximally Diverse Grouping Problem and its balanced version by the first objective, the students’ interests. The students’ interests are pictured by a preference sequence the students have for the offered seminars, e.g. because of the scheduled time, the topic or the lecturer. We present solution approaches that include properties from game theory in the assignment and result in an assignment of students to seminars including the students’ as well as the school’s preferences. Our results show that the presented solution approaches are able to solve instances of practical relevant size within half an hour (close to) optimality. Furthermore, in our artificial test instances, including student preferences in the assignment only led to a small reduction of the maximal diversity for instances of realistic size (2–3% difference for seminars with 20 students).</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1101 - 1124"},"PeriodicalIF":4.5000,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07189-8.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-026-07189-8","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The paper considers the assignment of students to seminars regarding three hierarchical objectives: maximizing the students’ preferences, maximizing the within seminar diversity, minimizing the between seminar diversity variation. While the first objective pictures the students, preferences, the second and third picture the school’s preference of having comparable seminar groups. To reach this aim the paper extends the well-known Maximally Diverse Grouping Problem and its balanced version by the first objective, the students’ interests. The students’ interests are pictured by a preference sequence the students have for the offered seminars, e.g. because of the scheduled time, the topic or the lecturer. We present solution approaches that include properties from game theory in the assignment and result in an assignment of students to seminars including the students’ as well as the school’s preferences. Our results show that the presented solution approaches are able to solve instances of practical relevant size within half an hour (close to) optimality. Furthermore, in our artificial test instances, including student preferences in the assignment only led to a small reduction of the maximal diversity for instances of realistic size (2–3% difference for seminars with 20 students).
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.