Approximate dynamic programming for the military inventory routing problem

Rebekah S. McKenna; Matthew J. Robbins; Brian J. Lunday; Ian M. McCormack

doi:10.1007/S10479-019-03469-8

Approximate dynamic programming for the military inventory routing problem

Rebekah S. McKenna
, Matthew J. Robbins
, Brian J. Lunday
, Ian M. McCormack

School of Technology

Air Force Institute of Technology

Producción científica › revisión exhaustiva

Idioma original	American English
Publicación	Annals of Operations Research
Volumen	288
DOI	https://doi.org/10.1007/S10479-019-03469-8
Estado	Published - may 1 2020

Disciplines

Applied Mathematics
Computer Sciences

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10.1007/S10479-019-03469-8Licencia: Unspecified

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https://doi.org/10.1007/s10479-019-03469-8

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title = "Approximate dynamic programming for the military inventory routing problem",

author = "McKenna, \{Rebekah S.\} and Robbins, \{Matthew J.\} and Lunday, \{Brian J.\} and McCormack, \{Ian M.\}",

note = "The United States Army can benefit from effectively utilizing cargo unmanned aerial vehicles (CUAVs) to perform resupply operations in combat environments to reduce the use of manned (ground and aerial) resupply that incurs risk to personnel. We formulate a Markov decision process (MDP) model of an inventory routing problem (IRP) with vehicle loss and direct delivery, which we label the military IRP (MILIRP).",

year = "2020",

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journal = "Annals of Operations Research",

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T1 - Approximate dynamic programming for the military inventory routing problem

AU - McKenna, Rebekah S.

AU - Robbins, Matthew J.

AU - Lunday, Brian J.

AU - McCormack, Ian M.

N1 - The United States Army can benefit from effectively utilizing cargo unmanned aerial vehicles (CUAVs) to perform resupply operations in combat environments to reduce the use of manned (ground and aerial) resupply that incurs risk to personnel. We formulate a Markov decision process (MDP) model of an inventory routing problem (IRP) with vehicle loss and direct delivery, which we label the military IRP (MILIRP).

PY - 2020/5/1

Y1 - 2020/5/1

UR - https://doi.org/10.1007/s10479-019-03469-8

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DO - 10.1007/S10479-019-03469-8

M3 - Article

VL - 288

JO - Annals of Operations Research

JF - Annals of Operations Research

ER -