Selection and Ordering Policies for Hiring Pipelines via Linear Programming
研究了企业在有限时间预算下，如何从应聘者中筛选面试人选并决定录用顺序，提出了非自适应近似算法，并分析了其与自适应算法的性能差距。
Hiring the right person for the job is crucial for the success of any organization. In “Selection and Ordering Policies for Hiring Pipelines via Linear Programming,” Epstein and Ma study several problems motivated by a firm that is carrying out a recruitment process. Restricted to a finite time budget, the firm must decide who will be interviewed out of a pool of applicants and who will receive offers among the interviewed applicants. They develop approximation algorithms with constant factor guarantees that approach optimality when the number of vacant positions grows large. The algorithms they develop are nonadaptive: they fix a subset of candidates and an order to conduct the interviews and the order remains unchanged, independent of the outcomes of other interviews. Thus, they establish bounds on the adaptivity gap: a worst-case measure of how poorly non-adaptive algorithms can perform with respect to their adaptive counterparts.