Mixed-Integer Linear Programming Models for Teaching Assistant Assignment and Extensions

Xiaobo Qu, Wen Yi, Tingsong Wang, Shuaian Wang, Lin Xiao, Zhiyuan Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant's teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a time-consuming process, does not need to be carried out in a manual manner. We have further presented a number of extensions that capture more practical considerations. Extensive numerical experiments show that the optimization models can be solved by an off-the-shelf solver and used by departments in universities.
Original languageEnglish
Article number9057947
JournalScientific Programming
Volume2017
DOIs
Publication statusPublished - 1 Jan 2017

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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