Rights statement: Copyright 2019 INFORMS
Accepted author manuscript, 474 KB, PDF document
Available under license: CC BY: Creative Commons Attribution 4.0 International License
Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Fast or Slow
T2 - Search in Discrete Locations with Two Search Modes
AU - Clarkson, Jake
AU - Glazebrook, Kevin David
AU - Lin, Kyle
N1 - Copyright 2019 INFORMS
PY - 2020/3/31
Y1 - 2020/3/31
N2 - 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 probabilitydistribution 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.
AB - 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 probabilitydistribution 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.
U2 - 10.1287/opre.2019.1870
DO - 10.1287/opre.2019.1870
M3 - Journal article
VL - 68
SP - 552
EP - 571
JO - Operations Research
JF - Operations Research
SN - 0030-364X
IS - 2
ER -