{"title":"Secretary problems with random number of candidates: How prior distributional information helps","authors":"Junhui Zhang, Patrick Jaillet","doi":"10.1016/j.ejor.2026.10.023","DOIUrl":null,"url":null,"abstract":"We study variants of the secretary problem, where <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mi>N</mml:mi></mml:math>, the number of candidates, is a random variable with distribution <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mi mathvariant=\"bold\">p</mml:mi></mml:math>. The decision maker, given prior distributional information about <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mi mathvariant=\"bold\">p</mml:mi></mml:math>, wants to maximize the probability of success – picking the largest number among the <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mi>N</mml:mi></mml:math> candidates – using only the sequentially revealed relative ranks of the candidates.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"74 1","pages":""},"PeriodicalIF":7.0000,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Operational Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1016/j.ejor.2026.10.023","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
We study variants of the secretary problem, where N, the number of candidates, is a random variable with distribution p. The decision maker, given prior distributional information about p, wants to maximize the probability of success – picking the largest number among the N candidates – using only the sequentially revealed relative ranks of the candidates.
期刊介绍:
The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.