TY - JOUR
T1 - Mixed-Integer Linear Programming Models for Teaching Assistant Assignment and Extensions
AU - Qu, Xiaobo
AU - Yi, Wen
AU - Wang, Tingsong
AU - Wang, Shuaian
AU - Xiao, Lin
AU - Liu, Zhiyuan
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85010299086&partnerID=8YFLogxK
U2 - 10.1155/2017/9057947
DO - 10.1155/2017/9057947
M3 - Journal article
SN - 1058-9244
VL - 2017
JO - Scientific Programming
JF - Scientific Programming
M1 - 9057947
ER -