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Sequential attack salvo size is monotonic nondecreasing in both time and inventory level

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Sequential attack salvo size is monotonic nondecreasing in both time and inventory level. / Kalyanam, K.; Clarkson, J.
In: Naval Research Logistics, Vol. 68, No. 4, 30.06.2021, p. 485-495.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Kalyanam K, Clarkson J. Sequential attack salvo size is monotonic nondecreasing in both time and inventory level. Naval Research Logistics. 2021 Jun 30;68(4):485-495. Epub 2020 Dec 21. doi: 10.1002/nav.21967

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Kalyanam, K. ; Clarkson, J. / Sequential attack salvo size is monotonic nondecreasing in both time and inventory level. In: Naval Research Logistics. 2021 ; Vol. 68, No. 4. pp. 485-495.

Bibtex

@article{0ad580c866c6469cbe276d4cbae9d976,
title = "Sequential attack salvo size is monotonic nondecreasing in both time and inventory level",
abstract = "An attacker with homogeneous weapons aims to destroy a target via sequential engagements over a finite planning horizon. Each weapon, with an associated cost, has a nonzero probability of destroying the target. At each decision epoch, the attacker can allocate a salvo of weapons to increase its chances, however this comes at the increasing linear cost of allocating additional weapons. We assume complete information in that the target status (dead or alive) is known. The attacker aims to maximize its chances of destroying the target while also minimizing the allocation cost. We show that the optimal salvo size, which is a function of time and inventory levels, is monotonic nondecreasing in both variables. In particular, we show that the salvo size either stays the same or decreases by one when the inventory level drops by one. The optimal allocation can be computed by solving a nonlinear stochastic dynamic program. Given the computational burden typically associated with solving Bellman recursions, we provide a scalable linear recursion to compute the optimal salvo size and numerical results to support the main ideas. ",
keywords = "sequential decision making, shoot-look-shoot, weapon-target assignment, Computer simulation, Ocean engineering, Complete information, Computational burden, Finite planning horizon, Function of time, Non-zero probability, Nonlinear stochastic dynamics, Numerical results, Optimal allocation, Stochastic systems",
author = "K. Kalyanam and J. Clarkson",
note = "This is the peer reviewed version of the following article: Kalyanam, K, Clarkson, J. Sequential attack salvo size is monotonic nondecreasing in both time and inventory level. Naval Research Logistics. 2021; 68: 485– 495. https://doi.org/10.1002/nav.21967 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/nav.21967 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving. ",
year = "2021",
month = jun,
day = "30",
doi = "10.1002/nav.21967",
language = "English",
volume = "68",
pages = "485--495",
journal = "Naval Research Logistics",
issn = "0894-069X",
publisher = "John Wiley and Sons Inc.",
number = "4",

}

RIS

TY - JOUR

T1 - Sequential attack salvo size is monotonic nondecreasing in both time and inventory level

AU - Kalyanam, K.

AU - Clarkson, J.

N1 - This is the peer reviewed version of the following article: Kalyanam, K, Clarkson, J. Sequential attack salvo size is monotonic nondecreasing in both time and inventory level. Naval Research Logistics. 2021; 68: 485– 495. https://doi.org/10.1002/nav.21967 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/nav.21967 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2021/6/30

Y1 - 2021/6/30

N2 - An attacker with homogeneous weapons aims to destroy a target via sequential engagements over a finite planning horizon. Each weapon, with an associated cost, has a nonzero probability of destroying the target. At each decision epoch, the attacker can allocate a salvo of weapons to increase its chances, however this comes at the increasing linear cost of allocating additional weapons. We assume complete information in that the target status (dead or alive) is known. The attacker aims to maximize its chances of destroying the target while also minimizing the allocation cost. We show that the optimal salvo size, which is a function of time and inventory levels, is monotonic nondecreasing in both variables. In particular, we show that the salvo size either stays the same or decreases by one when the inventory level drops by one. The optimal allocation can be computed by solving a nonlinear stochastic dynamic program. Given the computational burden typically associated with solving Bellman recursions, we provide a scalable linear recursion to compute the optimal salvo size and numerical results to support the main ideas.

AB - An attacker with homogeneous weapons aims to destroy a target via sequential engagements over a finite planning horizon. Each weapon, with an associated cost, has a nonzero probability of destroying the target. At each decision epoch, the attacker can allocate a salvo of weapons to increase its chances, however this comes at the increasing linear cost of allocating additional weapons. We assume complete information in that the target status (dead or alive) is known. The attacker aims to maximize its chances of destroying the target while also minimizing the allocation cost. We show that the optimal salvo size, which is a function of time and inventory levels, is monotonic nondecreasing in both variables. In particular, we show that the salvo size either stays the same or decreases by one when the inventory level drops by one. The optimal allocation can be computed by solving a nonlinear stochastic dynamic program. Given the computational burden typically associated with solving Bellman recursions, we provide a scalable linear recursion to compute the optimal salvo size and numerical results to support the main ideas.

KW - sequential decision making

KW - shoot-look-shoot

KW - weapon-target assignment

KW - Computer simulation

KW - Ocean engineering

KW - Complete information

KW - Computational burden

KW - Finite planning horizon

KW - Function of time

KW - Non-zero probability

KW - Nonlinear stochastic dynamics

KW - Numerical results

KW - Optimal allocation

KW - Stochastic systems

U2 - 10.1002/nav.21967

DO - 10.1002/nav.21967

M3 - Journal article

VL - 68

SP - 485

EP - 495

JO - Naval Research Logistics

JF - Naval Research Logistics

SN - 0894-069X

IS - 4

ER -