Prophet Secretary Against the Online Optimal

We study the prophet secretary problem, a well-studied variant of the classic prophet inequality, where values are drawn from independent known distributions but arrive in uniformly random order. Upon seeing a value at each step, the decision maker has to either select it and stop or irrevocably discard it. Traditionally, the chosen benchmark is the expected reward of the prophet, who knows all the values in advance and can always select the maximum one. In this work, we study the prophet secretary problem against a less pessimistic but equally well-motivated benchmark: the online optimal. Here, the main goal is to find polynomial-time algorithms that guarantee near-optimal expected reward. Our main result is a polynomial-time approximation scheme for this problem. The approximation scheme builds on careful discretization and bundling arguments, in combination with a novel “front-loading” technique that helps reduce the number of decisions the algorithm has to make.

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Publication Details

Journal
Mathematics of Operations Research
Published
2026-10-26
DOI
https://doi.org/10.1287/moor.2023.0252
Primary Topic
Optimization and Search Problems
Type
article
Field-Weighted Citation Impact
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article

Prophet Secretary Against the Online Optimal

Yifeng Teng, Rojin Rezvan, Alexandros Tsigonias-Dimitriadis, Evangelia Gergatsouli et al.
Mathematics of Operations Research
Optimization and Search Problems
article

Prophet Secretary Against the Online Optimal

Yifeng Teng, Rojin Rezvan, Alexandros Tsigonias-Dimitriadis, Evangelia Gergatsouli, Paul Dütting
article en

Abstract

We study the prophet secretary problem, a well-studied variant of the classic prophet inequality, where values are drawn from independent known distributions but arrive in uniformly random order. Upon seeing a value at each step, the decision maker has to either select it and stop or irrevocably discard it. Traditionally, the chosen benchmark is the expected reward of the prophet, who knows all the values in advance and can always select the maximum one. In this work, we study the prophet secretary problem against a less pessimistic but equally well-motivated benchmark: the online optimal. Here, the main goal is to find polynomial-time algorithms that guarantee near-optimal expected reward. Our main result is a polynomial-time approximation scheme for this problem. The approximation scheme builds on careful discretization and bundling arguments, in combination with a novel “front-loading” technique that helps reduce the number of decisions the algorithm has to make.

Mathematics of Operations Research
Google (United States) (US), University of Wisconsin–Madison (US), Google (Switzerland) (CH), University of Chile (CL), The University of Texas at Austin (US)
Openalex Percentile: Top 12%
Optimization and Search Problems
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