TY - GEN
T1 - Multi-Rank Smart Reserves
AU - Aziz, Haris
AU - Sun, Zhaohong
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/18
Y1 - 2021/7/18
N2 - We study the school choice problem where each school has flexible multi-ranked diversity goals, and each student may belong to multiple overlapping types, and consumes only one of the positions reserved for their types. We propose a novel choice function and show that it is the unique rule that satisfies three fundamental properties: maximal diversity, non-wastefulness, and justified envy-freeness. We provide a fast polynomial-time algorithm for our choice function that is based on the Dulmage Mendelsohn Decomposition Theorem as well as new insights into the combinatorial structure of constrained rank maximal matchings. Even for the case of minimum and maximum quotas for types (that capture two ranks), ours is the first known polynomial-time approach to compute an optimally diverse choice outcome. Finally, we prove that the choice function we design for schools, satisfies substitutability and hence can be directly embedded in the generalized deferred acceptance algorithm to achieve strategyproofness and stability. Our algorithms and results have immediate policy implications and directly apply to a variety of scenarios, such as where hiring positions or scarce medical resources need to be allocated while taking into account diversity concerns or ethical principles.
AB - We study the school choice problem where each school has flexible multi-ranked diversity goals, and each student may belong to multiple overlapping types, and consumes only one of the positions reserved for their types. We propose a novel choice function and show that it is the unique rule that satisfies three fundamental properties: maximal diversity, non-wastefulness, and justified envy-freeness. We provide a fast polynomial-time algorithm for our choice function that is based on the Dulmage Mendelsohn Decomposition Theorem as well as new insights into the combinatorial structure of constrained rank maximal matchings. Even for the case of minimum and maximum quotas for types (that capture two ranks), ours is the first known polynomial-time approach to compute an optimally diverse choice outcome. Finally, we prove that the choice function we design for schools, satisfies substitutability and hence can be directly embedded in the generalized deferred acceptance algorithm to achieve strategyproofness and stability. Our algorithms and results have immediate policy implications and directly apply to a variety of scenarios, such as where hiring positions or scarce medical resources need to be allocated while taking into account diversity concerns or ethical principles.
UR - http://www.scopus.com/inward/record.url?scp=85111985409&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111985409&partnerID=8YFLogxK
U2 - 10.1145/3465456.3467619
DO - 10.1145/3465456.3467619
M3 - Conference contribution
AN - SCOPUS:85111985409
T3 - EC 2021 - Proceedings of the 22nd ACM Conference on Economics and Computation
SP - 105
EP - 124
BT - EC 2021 - Proceedings of the 22nd ACM Conference on Economics and Computation
PB - Association for Computing Machinery, Inc
T2 - 22nd ACM Conference on Economics and Computation, EC 2021
Y2 - 18 July 2021 through 23 July 2021
ER -