Home > Research > Publications & Outputs > Fast or Slow

Electronic data

  • Two Speed Search

    Rights statement: Copyright 2019 INFORMS

    Accepted author manuscript, 474 KB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Fast or Slow: Search in Discrete Locations with Two Search Modes

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>31/03/2020
<mark>Journal</mark>Operations Research
Issue number2
Volume68
Number of pages20
Pages (from-to)552-571
Publication StatusPublished
Early online date7/01/20
<mark>Original language</mark>English

Abstract

An object is hidden in one of several discrete locations according to some known probability distribution, and the goal is to discover the object in minimum expected time by successive searches of individual locations. If there is only one way to search each location, this search problem is solved using Gittins indices. Motivated by modern search technology, we extend earlier work to allow two modes—fast and slow—to search each location. The fast mode takes less time, but the slow mode is more likely to find the object. An optimal policy is difficult to obtain in general, because it requires an optimal sequence of search modes for each location, in addition to a set of sequence-dependent Gittins indices for choosing between locations. Our analysis begins by—for each mode—identifying a sufficient condition for a location to use only that search mode in an optimal policy. For locations meeting neither sufficient condition, an optimal choice of search mode is extremely complicated, depending both on the probability
distribution of the object’s hiding location and the search parameters of the other locations. We propose several heuristic policies motivated by our analysis, and demonstrate their near-optimal performance in an extensive numerical study.

Bibliographic note

Copyright 2019 INFORMS