June 15, 2019
June 15, 2019
June 19, 2019
The chemical engineering program at The Ohio State University has been growing rapidly over the last decade, and it is now one of the largest in the United States. Students enroll in Unit Operations for two semesters, making the course twice the size of other courses in the department; enrollment is typically about 220 students in the combined lab/lecture course. To cope with the growing enrollment, the course instructors have adopted a number of time-saving strategies.
The most successful of these strategies has been the development and use of an evolutionary algorithm to assign students into groups and schedule those groups in the laboratory. The evolutionary algorithm makes random changes to the group assignments and lab schedule and keeps beneficial changes as measured by ten criteria. Data are presented for one recent semester in which the algorithm was successfully used for group assignment and scheduling with an enrollment of 225 students in 48 groups, each completing 2 of 15 experiments available in the lab.
A working example of the algorithm has been made publicly available for download. It was implemented in Microsoft Excel so that no special software installation or licensing is required, and so that anyone familiar with writing worksheet formulas in Excel can easily customize the algorithm for their own use.
The full algorithm (225 students, 48 groups, 12 experiments, and 10 criteria) reached an acceptable solution after about 9 hours of computing time, while the simpler working example provided by the author (72 students, 18 groups, 5 experiments, and 4 criteria) reaches a near optimal solution in about 10 seconds.
Maxson, A. (2019, June), A Time-Saving Algorithm for Team Assignment and Scheduling in a Large-Scale Unit Operations Laboratory Course Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. https://peer.asee.org/32014
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