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Research on construction and task planning of police equipment support system based on background of anti-terrorism operation

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  • Qilei Wang

    (China People’s Police University)

Abstract

In order to ensure the operational efficiency of police personnel under the background of anti-terrorism operation, this paper puts forward the planning and construction method of equipment support system for task demand, and constructs the anti-terrorism equipment support system in Xinjiang region Combined with the constructed system, a mathematical model with time-priority as the objective is established, and a hybrid task planning method based on multidimensional dynamic list programming and chaotic bat algorithm is proposed. A discrete chaotic bat algorithm with adaptive search strategy and mutation operation is designed to allocate resources for selected tasks by multidimensional dynamic list tasks. The research shows that the established support system fully considers the equipment system demand generation mechanism under the Background of anti-terrorism operation, and increases the introduction of the support system and the technical standard system, which can effectively meet the personnel equipment support needs in the anti-terrorism environment.

Suggested Citation

  • Qilei Wang, 2024. "Research on construction and task planning of police equipment support system based on background of anti-terrorism operation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2730-2742, June.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:6:d:10.1007_s13198-024-02296-w
    DOI: 10.1007/s13198-024-02296-w
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    References listed on IDEAS

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    1. Boutselis, Petros & McNaught, Ken, 2019. "Using Bayesian Networks to forecast spares demand from equipment failures in a changing service logistics context," International Journal of Production Economics, Elsevier, vol. 209(C), pages 325-333.
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