Wyne, M., & Farahani, A., & Atashpaz-Gargari, E., & Zhang, L. (2022, August), Multi-Semester Course Staffing Optimization  Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41754

\bibitem{asee_peer_41754}
  Wyne, M., \& Farahani, A., \& Atashpaz-Gargari, E., \& Zhang, L. (2022, August), \emph{Multi-Semester Course Staffing Optimization}
  Paper presented at 2022 ASEE Annual Conference \& Exposition, Minneapolis, MN.
  10.18260/1-2--41754

Mudasser Wyne, Alireza Farahani, Esmaeil Atashpaz-Gargari, and Lu Zhang.  "Multi-Semester Course Staffing Optimization".  2022 ASEE Annual Conference & Exposition, Minneapolis, MN, 2022, August.  ASEE Conferences, 2022.  https://peer.asee.org/41754 Internet.  30 Apr, 2024

\bibitem{asee_peer_41754}
  Mudasser Wyne, Alireza Farahani, Esmaeil Atashpaz-Gargari, and Lu Zhang.
  "Multi-Semester Course Staffing Optimization".
  \emph{2022 ASEE Annual Conference \& Exposition, Minneapolis, MN, 2022, August}.
  ASEE Conferences, 2022.
  https://peer.asee.org/41754 Internet.  30 Apr, 2024

@INPROCEEDINGS{asee_peer_41754
author = "Mudasser Wyne, Alireza Farahani, Esmaeil Atashpaz-Gargari, and Lu Zhang"
title = "Multi-Semester Course Staffing Optimization"
booktitle = "2022 ASEE Annual Conference \& Exposition"
year = "2022"
month = "August"
address = "Minneapolis, MN"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/41754}
number = {10.18260/1-2--41754}
}

TY  - CPAPER
AB  - Course scheduling and staffing is a problem that academic institutions need to solve every semester or quarter. The problem can be formulated as a combinatorial problem to produce optimal course schedules and/or staffing assignments by assigning classes to faculty members while meeting multiple constraints. The objective for the program director or the department chair is to find an optimal solution for class staffing considering different constraints. These constraints include faculty availability, qualification, and teaching preferences. Conflict in days and hours when faculty are available is the intrinsic nature of the underlying problem. Teaching load is also an essential constraint. During an academic year, each faculty member must meet a minimum and maximum number of classes to teach.
Typically, the scope of the scheduling and staffing problem is a single semester or a quarter. However, some universities with accelerated programs offer courses in a unique Accelerated Term (AT) format that spans over multiple weeks (e.g., four, six, or eight weeks). Under a traditional university setting, this is equivalent to staffing instructors across multiple semesters or quarters. Therefore, in addition to the multi-criteria combinatorial complexity, the problem is further complicated by attempting to optimize course assignments across multiple accelerated terms within an academic year.
In this paper, we present a course staffing solution that optimizes the assignment of faculty to classes across multiple accelerated terms in the scope of an academic year. The ultimate goal is to efficiently and effectively allocate instructors to courses that meet all the constraints but favor allocating courses to instructors who are highly qualified and interested in teaching the subject. The optimality of the solutions is determined by an objective function that is formulated into the problem statement along with the constraints.
AU  - Mudasser Wyne
AU  - Alireza Farahani
AU  - Esmaeil Atashpaz-Gargari
AU  - Lu Zhang
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Multi-Semester Course Staffing Optimization
UR  - https://peer.asee.org/41754
DO  - 10.18260/1-2--41754
ER  -