Order Selection Prophet Inequality

Abstract. In the classical prophet inequality, a gambler faces a sequence of items, whose values are drawn independently from known distributions. Upon the arrival of each item, its value is realized and the gambler either accepts it and the game ends, or irrevocably rejects it and continues to the next item. The goal is to maximize the value of the selected item and compete against the expected maximum value of all items. A tight competitive ratio of [Formula: see text] is established in the classical setting and various relaxations have been proposed to surpass the barrier, including the i.i.d. model, the order selection model, and the random order model. In this paper, we advance the study of the order selection prophet inequality, in which the gambler is given the extra power for selecting the arrival order of the items. Our main result is a 0.725-competitive algorithm, that substantially improves the state-of-the-art 0.669 ratio by Correa, Saona, and Ziliotto [ Math. Program., 190 (2021), pp. 483–521], achieved in the harder random order model. Recently, Agrawal, Sethuraman, and Zhang [ On optimal ordering in the optimal stopping problem, EC’20: Proceedings of the 21st ACM Conference on Economics and Computation, ACM, New York, 2020, pp. 187–188] proved that the task of selecting the optimal order is NP-hard. Despite this fact, we introduce a novel algorithm design framework that translates the discrete order selection problem into a continuous arrival time design problem. From this perspective, we can focus on the arrival time design without worrying about the threshold optimization afterwards. As a side result, we achieve the optimal 0.745 competitive ratio by applying our algorithm to the i.i.d. model.

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Publication Details

Journal
SIAM Journal on Computing
Published
2026-11-03
DOI
https://doi.org/10.1137/23m1623574
Primary Topic
Optimization and Search Problems
Type
article
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article

Order Selection Prophet Inequality

Zhihao Gavin Tang, Bo Peng
SIAM Journal on Computing
Optimization and Search Problems
article

Order Selection Prophet Inequality

Zhihao Gavin Tang, Bo Peng
article en

Abstract

Abstract. In the classical prophet inequality, a gambler faces a sequence of items, whose values are drawn independently from known distributions. Upon the arrival of each item, its value is realized and the gambler either accepts it and the game ends, or irrevocably rejects it and continues to the next item. The goal is to maximize the value of the selected item and compete against the expected maximum value of all items. A tight competitive ratio of [Formula: see text] is established in the classical setting and various relaxations have been proposed to surpass the barrier, including the i.i.d. model, the order selection model, and the random order model. In this paper, we advance the study of the order selection prophet inequality, in which the gambler is given the extra power for selecting the arrival order of the items. Our main result is a 0.725-competitive algorithm, that substantially improves the state-of-the-art 0.669 ratio by Correa, Saona, and Ziliotto [ Math. Program., 190 (2021), pp. 483–521], achieved in the harder random order model. Recently, Agrawal, Sethuraman, and Zhang [ On optimal ordering in the optimal stopping problem, EC’20: Proceedings of the 21st ACM Conference on Economics and Computation, ACM, New York, 2020, pp. 187–188] proved that the task of selecting the optimal order is NP-hard. Despite this fact, we introduce a novel algorithm design framework that translates the discrete order selection problem into a continuous arrival time design problem. From this perspective, we can focus on the arrival time design without worrying about the threshold optimization afterwards. As a side result, we achieve the optimal 0.745 competitive ratio by applying our algorithm to the i.i.d. model.

SIAM Journal on ComputingVol. 55(6)
Shanghai University of Finance and Economics (CN)
Openalex Percentile: Top 15%
Optimization and Search Problems
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Order Selection Prophet Inequality — Zhihao Gavin Tang, Bo Peng · SIAM Journal on Computing (2026) | TGRS Research Map | TGRS