Team formation using fair allocation

Though team formation is an inherently practical problem, it is rarely formulated as such due to its high complexity. The aim of this thesis is to formulate team formation in a practical way, using the principles of fair allocation to develop effective and efficient methods of forming teams. We begin by examining the fields of diversity research, fair allocation, and team formation, showing that these research areas are closely linked. We then present a setting in which team formation can be easily modeled as a practical problem, and present algorithms to address team formation within this new setting. Though our algorithms evaluate resulting teams on established fairness principles, they cannot guarantee perfect, or even the best solutions. However, unlike many existing algorithms for team formation, our algorithms have runtimes that make them practicable for everyday use. Accordingly, we developed a tool which can be integrated with the Canvas LMS environment to enable instructors to make use of our team formation algorithms for their classes, and present the results of several pilot studies to demonstrate its viability. Our pilot studies provide useful feedback on our tool, as well as showing the viability of our algorithms as practical methods of team formation.Science, Irving K. Barber Faculty of (Okanagan)Computer Science, Mathematics, Physics and Statistics, Department of (Okanagan)Graduat