Order-selection Prophet Inequality (Almost) Goes I.I.D

We study the order-selection prophet inequality. A gambler knows the distributions of independent nonnegative random values, chooses the order in which to inspect them, and may irrevocably accept at most one value, at the time it is revealed. Since the order is irrelevant when the values are i.i.d., no algorithm can guarantee more than the optimal i.i.d.\ ratio $Γ_\star\approx0.74544$ of the expected maximum. We give an algorithm with competitive ratio $0.74500001$, less than $4.5\times10^{-4}$ below this bound. The algorithm samples independent arrival times and uses item-dependent thresholds. It is designed so that, conditional on its value, every item is selected with probability equal to a fixed fraction of its probability of being the maximum. We show that the constructions of this form that apply one local rule to every item are exactly those given by an allocation kernel, that is, by a coupling of two uniform random variables. Requiring every rarely winning item to follow the optimal i.i.d.\ threshold path singles out a baseline kernel, for which we prove analytically a ratio $Γ_0\approx0.7389$, defined through a one-dimensional control problem. Our final kernel perturbs this baseline, and its guarantee combines analytic estimates with a rigorous computer-assisted certificate.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.34892
Primary Topic
Optimization and Search Problems
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Order-selection Prophet Inequality (Almost) Goes I.I.D

Zhihao Gavin Tang, Bo Peng
arXiv (Cornell University)
Optimization and Search Problems
preprint

Order-selection Prophet Inequality (Almost) Goes I.I.D

Zhihao Gavin Tang, Bo Peng
preprint en

Abstract

We study the order-selection prophet inequality. A gambler knows the distributions of independent nonnegative random values, chooses the order in which to inspect them, and may irrevocably accept at most one value, at the time it is revealed. Since the order is irrelevant when the values are i.i.d., no algorithm can guarantee more than the optimal i.i.d.\ ratio $Γ_\star\approx0.74544$ of the expected maximum. We give an algorithm with competitive ratio $0.74500001$, less than $4.5\times10^{-4}$ below this bound. The algorithm samples independent arrival times and uses item-dependent thresholds. It is designed so that, conditional on its value, every item is selected with probability equal to a fixed fraction of its probability of being the maximum. We show that the constructions of this form that apply one local rule to every item are exactly those given by an allocation kernel, that is, by a coupling of two uniform random variables. Requiring every rarely winning item to follow the optimal i.i.d.\ threshold path singles out a baseline kernel, for which we prove analytically a ratio $Γ_0\approx0.7389$, defined through a one-dimensional control problem. Our final kernel perturbs this baseline, and its guarantee combines analytic estimates with a rigorous computer-assisted certificate.

arXiv (Cornell University)
Optimization and Search Problems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Order-selection Prophet Inequality (Almost) Goes I.I.D — Zhihao Gavin Tang, Bo Peng · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS