TY - JOUR
T1 - Strategyproof Mechanism for Two-Sided Matching with Resource Allocation
AU - Liu, Kwei guu
AU - Yahiro, Kentaro
AU - Yokoo, Makoto
N1 - Funding Information:
This work is partially supported by the joint project with Toyota Motor Corporation , titled “Advanced Mathematical Science for Mobility Society”, and JSPS KAKENHI Grant Numbers JP20H00609 and JP21H04979 .
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/3
Y1 - 2023/3
N2 - In this work, we consider a student-project-resource matching-allocation problem, where students have preferences over projects and the projects have preferences over students. In this problem, students and indivisible resources are many-to-one matched to projects whose capacities are endogenously determined by the resources allocated to them. Traditionally, this problem is decomposed into two separate problems: (1) resources are allocated to projects based on expectations (a resource allocation problem), and (2) students are matched to projects based on the capacities determined in the previous problem (a matching problem). Although both problems are well-understood, if the expectations used in the first are incorrect, we obtain a sub-optimal outcome. Thus, this problem should be solved as a whole without dividing it into two parts. We show that no strategyproof mechanism satisfies fairness and weak efficiency requirements. Given this impossibility result, we develop a new class of strategyproof mechanisms called Sample and Deferred Acceptance (SDA), which satisfies several properties on fairness and efficiency. We experimentally compare several SDA instances as well as existing mechanisms, and show that an SDA instance strikes a good balance of fairness and efficiency when students are divided into different types according to their preferences.
AB - In this work, we consider a student-project-resource matching-allocation problem, where students have preferences over projects and the projects have preferences over students. In this problem, students and indivisible resources are many-to-one matched to projects whose capacities are endogenously determined by the resources allocated to them. Traditionally, this problem is decomposed into two separate problems: (1) resources are allocated to projects based on expectations (a resource allocation problem), and (2) students are matched to projects based on the capacities determined in the previous problem (a matching problem). Although both problems are well-understood, if the expectations used in the first are incorrect, we obtain a sub-optimal outcome. Thus, this problem should be solved as a whole without dividing it into two parts. We show that no strategyproof mechanism satisfies fairness and weak efficiency requirements. Given this impossibility result, we develop a new class of strategyproof mechanisms called Sample and Deferred Acceptance (SDA), which satisfies several properties on fairness and efficiency. We experimentally compare several SDA instances as well as existing mechanisms, and show that an SDA instance strikes a good balance of fairness and efficiency when students are divided into different types according to their preferences.
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U2 - 10.1016/j.artint.2023.103855
DO - 10.1016/j.artint.2023.103855
M3 - Article
AN - SCOPUS:85146098653
SN - 0004-3702
VL - 316
JO - Artificial Intelligence
JF - Artificial Intelligence
M1 - 103855
ER -