An Efficient Approximate Solution for Stochastic Lanchester Models

12 Pages Posted: 24 Apr 2018

See all articles by Donghyun Kim

Donghyun Kim

University of Wisconsin - Milwaukee

Hyungil Moon

Korea Advanced Institute of Science and Technology (KAIST)

Hayong Shin

Korea Advanced Institute of Science and Technology (KAIST)

Donghyun Park

Nanyang Technological University (NTU); Asian Development Bank

Date Written: February 2017

Abstract

Combat modeling is one of the essential topics for military decision making. The Lanchester equation is a classic method for modeling warfare, and many variations have extended its limitations and relaxed its assumptions. As a model becomes more complex, solving it analytically becomes intractable or computationally expensive. Hence, we propose two approximation methods: moment-matching scheme and a supporting method called battle-end approximation. These methods give an approximate solution in a short amount of time, while maintaining a high level of accuracy in simulation results in terms of hypothesis testing and numerical verification. They can be applied to computationally intensive problems, such as optimal resource allocation and analysis with asymmetric power like snipers or stealth aircrafts.

Keywords: Military, stochastic Lanchester model, Gaussian approximation

Suggested Citation

Kim, Donghyun and Moon, Hyungil and Shin, Hayong and Park, Donghyun, An Efficient Approximate Solution for Stochastic Lanchester Models (February 2017). Journal of the Operational Research Society, Vol. 68, Issue 11, 2017. Available at SSRN: https://ssrn.com/abstract=3161465 or http://dx.doi.org/10.1057/s41274-016-0163-6

Donghyun Kim (Contact Author)

University of Wisconsin - Milwaukee ( email )

Bolton Hall 802
3210 N. Maryland Ave.
Milwaukee, WI 53211
United States

Hyungil Moon

Korea Advanced Institute of Science and Technology (KAIST)

373-1 Kusong-dong
Yuson-gu
Taejon 305-701, 130-722
Korea, Republic of (South Korea)

Hayong Shin

Korea Advanced Institute of Science and Technology (KAIST) ( email )

373-1 Kusong-dong
Yuson-gu
Taejon 305-701, 130-722
Korea, Republic of (South Korea)

Donghyun Park

Nanyang Technological University (NTU) ( email )

S3 B2-A28 Nanyang Avenue
Singapore, 639798
Singapore

Asian Development Bank

6 ADB Avenue, Mandaluyong City 1550
Metro Manila
Philippines

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