Hierarchical optimal configuration model and algorithm for counterterrorism resource allocation

Chenmei Teng, Yin Xiang (), Shanliang Li (), Ronald McIver, Poshan Yu and Jinglan Gong
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Chenmei Teng: Suzhou City University
Yin Xiang: Suzhou University of Science and Technology
Shanliang Li: Soochow University
Ronald McIver: University of South Australia
Poshan Yu: Soochow University
Jinglan Gong: University of Science and Technology of China

Humanities and Social Sciences Communications, 2025, vol. 12, issue 1, 1-14

Abstract: Abstract Counterterrorism resource allocation is a critical challenge, especially under financial constraints. Traditional location-allocation models often overlook the hierarchical structure of counterterrorism resources and the evolution of dynamic demand, resulting in inefficient emergency responses. To address this gap, this study proposes a hierarchical configuration model to optimize the location of facilities and the allocation of counterterrorism resources under budget limitations, explicitly incorporating dynamic collaborative strategies. An improved algorithm is developed to significantly increase computational efficiency and reduce model complexity. The results demonstrate that hierarchical structures provide greater flexibility and cost-effectiveness than nonhierarchical approaches do. Moreover, the integration of dynamic collaborative strategies effectively reduces disutility and financial expenditures, which substantially improves emergency response efficiency in counterterrorism scenarios. The proposed model has practical implications for counterterrorism planning, urban security, and critical infrastructure protection, offering valuable insights into improving resource allocation and emergency response capabilities in real-world applications.

Date: 2025
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DOI: 10.1057/s41599-025-04988-5

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