Application of TTC and TTAS Mechanisms in Bed Allocation Problem in Chinese Universities

Abstract

Dormitory beds are assigned to students at random in China each year. However, a big majority of students are dissatisfied with their results, which will have an impact on their academic performance. The goal of this paper is to help students choose a suitable bed by using an algorithm after the initial allocation. This research constructs a bed allocation model and firstly employ the top trading cycles algorithm, which fulfills individual rationality, Pareto-efficiency, and strategy-proofness. Notwithstanding, this paper finds that the chance of indifferences cannot be precluded, despite the fact that this article let students rank beds as indicated by their inclinations for rooms and beds. Subsequently, the top trading cycles algorithm is ineffectual for this issue. The top trading absorbing sets algorithm is then applied to the general domain to create individual rationally, Pareto-efficient, and strategy-proof matching. This paper finds that the top trading absorbing sets algorithm is a suitable solution for bed allocation problem in Chinese universities and suggests universities to apply this algorithm after randomly allocating beds to freshmen to enhance the satisfaction of students.