Legal Assignments and Fast EADAM with Consent via Classic Theory of Stable Matchings

Oper. Res. Pub Date : 2022-01-24 DOI:10.1287/opre.2021.2199
Yuri Faenza, Xuan Zhang
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Abstract

Since the seminal work of Gale and Shapley, stable assignments have received widespread attention for their mathematical elegance and broad applicability. However, in applications such as the school choice problem, in which public schools are often perceived as commodities and only students’ welfare matters, enforcing stability implies a loss of efficiency for the students. In “Legal assignments and fast EADAM with consent via classical theory of stable matchings,” Faenza and Zhang study two extensions of the traditional model—legal assignments and efficiency adjusted deferred acceptance mechanism (EADAM)—that strive to regain this loss in efficiency. The authors establish a tight connection between legal and stable assignments, which allows them to use critical structural tools of stable matchings, such as the concept of rotations, to design provably fast algorithms for (1) optimizing linear functions over the set of legal assignments and (2) finding the outcome of EADAM. These algorithmic results greatly improve the applicability of both extensions as witnessed by a complexity analysis and experimental results.
基于经典稳定匹配理论的法律转让与快速EADAM
自从Gale和Shapley的开创性工作以来,稳定分配因其数学上的优雅和广泛的适用性而受到广泛的关注。然而,在学校选择问题等应用中,公立学校往往被视为商品,只关心学生的福利,加强稳定意味着学生效率的损失。在“经典稳定匹配理论下的法律分配和快速EADAM”一文中,Faenza和Zhang研究了传统模型的两个扩展——法律分配和效率调整延迟接受机制(EADAM)——努力弥补这种效率上的损失。作者建立了合法分配和稳定分配之间的紧密联系,这使得他们能够使用稳定匹配的关键结构工具,例如旋转的概念,来设计可证明的快速算法,用于(1)在合法分配集合上优化线性函数和(2)找到EADAM的结果。从复杂度分析和实验结果可以看出,这些算法结果大大提高了两种扩展的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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