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

Author:

Qu Xiaobo1ORCID,Yi Wen2,Wang Tingsong3ORCID,Wang Shuaian4ORCID,Xiao Lin5,Liu Zhiyuan6ORCID

Affiliation:

1. School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia

2. Department of Building and Real Estate, The Hong Kong Polytechnic University, Kowloon, Hong Kong

3. School of Economics and Management, Wuhan University, Wuhan 430072, China

4. Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong

5. National Research Council of the National Research Academies of Science, Engineering, and Medicine, Washington, DC 20001, USA

6. Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Jiangsu, China

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

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