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High-end weapon equipment portfolio selection based on a heterogeneous network model

Author

Listed:
  • Jichao Li

    (National University of Defense Technology
    Northwestern University
    Northwestern University)

  • Bingfeng Ge

    (National University of Defense Technology)

  • Jiang Jiang

    (National University of Defense Technology)

  • Kewei Yang

    (National University of Defense Technology)

  • Yingwu Chen

    (National University of Defense Technology)

Abstract

The selection and development of high-end weapon equipment is a strategic issue for nations. High-end weapon equipment portfolio selection (HWEPS) has attracted much attention because it is closely related to the production, deployment, and operation of weapons, which is a crucial factor determining the outcome of a war. This paper presents a united framework called capability-oriented weapon system portfolio selection (CWSPS) to solve the HWEPS problem based on a heterogeneous combat network. Specifically, the concept of an operation loop is introduced and a heterogeneous combat network model is proposed, with consideration of the different types of functional entities and information flows of high-end weapon equipment systems. Based on this, a new measure called the operational capability evaluation index (OCEI) is first proposed to assess the operational execution capability of a portfolio of high-end equipment systems. Then, a portfolio selection model is established by maximizing the cost-OCEI efficiency of high-end weapon equipment, with capability demand and the budget restriction as constraints. Finally, both an empirical case of missile defense system and numerical experiments are taken to demonstrate the reliability and effectiveness of CWSPS, and results show that our method can achieve very good performance in solving the HWEPS problem.

Suggested Citation

  • Jichao Li & Bingfeng Ge & Jiang Jiang & Kewei Yang & Yingwu Chen, 2020. "High-end weapon equipment portfolio selection based on a heterogeneous network model," Journal of Global Optimization, Springer, vol. 78(4), pages 743-761, December.
    • Handle: RePEc:spr:jglopt:v:78:y:2020:i:4:d:10.1007_s10898-018-0687-1
    DOI: 10.1007/s10898-018-0687-1
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    References listed on IDEAS

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