Research on weapon system portfolio selection based on combat network modeling

Joint operations and combat system-of-systems encounter have become major developing trends of modern warfare. Weapon system portfolio selection attracts much attention, because it is closely related to the production, deployment and operation of weapons, which is a crucial factor determining the ou...

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Bibliographic Details
Published in2017 Annual IEEE International Systems Conference (SysCon) pp. 1 - 6
Main Authors Cheng Cheng, Jichao Li, Qingsong Zhao, Jiang Jiang, Lixin Yu, Huilin Shang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2017
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Summary:Joint operations and combat system-of-systems encounter have become major developing trends of modern warfare. Weapon system portfolio selection attracts much attention, because it is closely related to the production, deployment and operation of weapons, which is a crucial factor determining the outcome of the war. This paper presents a portfolio selection model of the weapon systems based on the combat network. Firstly, we describe the portfolio selection problem of weapon systems based on the combat network, introduce the concept of operation loop, and analyze difficulties and strategies of the optimization problem. Then on this basis, the combat network of the weapon equipment system is modeled, and the operational capability evaluation index of weapon system-of-systems based on the operational loop is constructed. Portfolio selection model based on combat network is established to maximize the combined combat capability of the weapon as an optimization target, and the capacity demand and the expense restriction as constraints. Finally, we take the missile defense system as a example to demonstrate the whole calculation process and results of the weapon system portfolio selection based on the combat network model. It shows that our proposed method can achieve a very good performance to solve weapon system portfolio selection problems.
ISSN:2472-9647
DOI:10.1109/SYSCON.2017.7934733