Publication: A Fast-Pivoting Algorithm for Whittle's Restless Bandit Index
dc.affiliation.dpto | UC3M. Departamento de Estadística | es |
dc.contributor.author | Niño Mora, José | |
dc.contributor.funder | Ministerio de Educación y Ciencia (España) | es |
dc.date.accessioned | 2021-07-06T07:40:07Z | |
dc.date.available | 2021-07-06T07:40:07Z | |
dc.date.issued | 2020-12 | |
dc.description | This article belongs to the Special Issue Applied Probability | en |
dc.description.abstract | The Whittle index for restless bandits (two-action semi-Markov decision processes) provides an intuitively appealing optimal policy for controlling a single generic project that can be active (engaged) or passive (rested) at each decision epoch, and which can change state while passive. It further provides a practical heuristic priority-index policy for the computationally intractable multi-armed restless bandit problem, which has been widely applied over the last three decades in multifarious settings, yet mostly restricted to project models with a one-dimensional state. This is due in part to the difficulty of establishing indexability (existence of the index) and of computing the index for projects with large state spaces. This paper draws on the author’s prior results on sufficient indexability conditions and an adaptive-greedy algorithmic scheme for restless bandits to obtain a new fast-pivoting algorithm that computes the n Whittle index values of an n-state restless bandit by performing, after an initialization stage, n steps that entail (2/3)n3+O(n2) arithmetic operations. This algorithm also draws on the parametric simplex method, and is based on elucidating the pattern of parametric simplex tableaux, which allows to exploit special structure to substantially simplify and reduce the complexity of simplex pivoting steps. A numerical study demonstrates substantial runtime speed-ups versus alternative algorithms. | en |
dc.description.sponsorship | This research has been developed over a number of years, and has been funded by the Spanish Government under grants MEC MTM2004-02334 and PID2019-109196GB-I00/AEI/10.13039/501100011033. This research was also funded in part by the Comunidad de Madrid in the setting of the multi-year agreement with Universidad Carlos III de Madrid within the line of activity "Excelencia para el Profesorado Universitario", in the framework of the V Regional Plan of Scientific Research and Technological Innovation 2016-2020. | en |
dc.format.extent | 21 | |
dc.identifier.bibliographicCitation | Niño-Mora, J. (2020). A Fast-Pivoting Algorithm for Whittle’s Restless Bandit Index. Mathematics, 8(12), 2226. | en |
dc.identifier.doi | https://doi.org/10.3390/math8122226 | |
dc.identifier.issn | 2227-7390 | |
dc.identifier.publicationfirstpage | 2226 | |
dc.identifier.publicationissue | 12 | |
dc.identifier.publicationtitle | Mathematics | en |
dc.identifier.publicationvolume | 8 | |
dc.identifier.uri | https://hdl.handle.net/10016/33001 | |
dc.identifier.uxxi | AR/0000026986 | |
dc.language.iso | eng | |
dc.publisher | MDPI | |
dc.relation.projectID | Gobierno de España. PID2019-109196GB-I00 | es |
dc.relation.projectID | Gobierno de España. MTM2004-02334 | es |
dc.rights | © 2020 by the author. | en |
dc.rights | Atribución 3.0 España | * |
dc.rights.accessRights | open access | en |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject.eciencia | Estadística | es |
dc.subject.other | Restless bandits | en |
dc.subject.other | Whittle index | en |
dc.subject.other | Stochastic scheduling | en |
dc.subject.other | Index policies | en |
dc.subject.other | Indexability | en |
dc.subject.other | Index algorithm | en |
dc.subject.other | Markov decision processes | en |
dc.title | A Fast-Pivoting Algorithm for Whittle's Restless Bandit Index | en |
dc.type | research article | * |
dc.type.hasVersion | VoR | * |
dspace.entity.type | Publication |
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