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<p>While hybrid simulation methods (HSMs)—integrating Agent-Based Modeling (ABM), Discrete Event Simulation (DES), and System Dynamics (SD)—have gained increasing research attention for their comprehensive analytical capabilities, the field currently lacks a coherent framework to guide the selection of modeling types and interaction mechanisms. Existing studies often adopt technically feasible combinations without sufficient theoretical justification, particularly in aligning methodological choices with specific research questions and system characteristics. This review systematically analyzes 242 HSM publications to map the conceptual terrain and identify critical research gaps. We find that “ABM+DES” dominates the literature (57.14%), primarily employing bidirectional interaction mechanisms (“ABM&lt;-&gt;DES”) to bridge micro-level agent behaviors with macro-level system dynamics. However, this prevalence reflects methodological convenience rather than theoretical optimization, as evidenced by the underutilization of other potentially valuable combinations like “ABM+SD” (3.27%). The field predominantly applies HSMs for “simulation and evaluation” with descriptive aims, revealing a significant gap in prescriptive and optimization-oriented applications. Furthermore, despite validation challenges, only 53.72% of studies implement systematic validation strategies, indicating methodological immaturity. The most pressing limitation concerns “model generalizability,” stemming from context-specific implementations without transferable frameworks. Finally, based on the existing literature review and in combination Large Language Models (LLMs), the future development trends of HSM are further analyzed to address the current limitations in model construction, validation, and operational efficiency, while establishing a stronger theoretical foundation for method selection and application.</p>

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A Systematic Review and Prospect of Hybrid Simulation Methods and Applications from 1980 to 2024

  • 期刊论文

  • 发表日期：

    2026年6月1日

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  • Fengwei Jia,
  • Hongli Zhu,
  • Fengyuan Jia,
  • Changyan Shih,
  • Zhaosheng Yao,
  • Shiyong Liu,
  • Wai Kin Chan

摘要

While hybrid simulation methods (HSMs)—integrating Agent-Based Modeling (ABM), Discrete Event Simulation (DES), and System Dynamics (SD)—have gained increasing research attention for their comprehensive analytical capabilities, the field currently lacks a coherent framework to guide the selection of modeling types and interaction mechanisms. Existing studies often adopt technically feasible combinations without sufficient theoretical justification, particularly in aligning methodological choices with specific research questions and system characteristics. This review systematically analyzes 242 HSM publications to map the conceptual terrain and identify critical research gaps. We find that “ABM+DES” dominates the literature (57.14%), primarily employing bidirectional interaction mechanisms (“ABM<->DES”) to bridge micro-level agent behaviors with macro-level system dynamics. However, this prevalence reflects methodological convenience rather than theoretical optimization, as evidenced by the underutilization of other potentially valuable combinations like “ABM+SD” (3.27%). The field predominantly applies HSMs for “simulation and evaluation” with descriptive aims, revealing a significant gap in prescriptive and optimization-oriented applications. Furthermore, despite validation challenges, only 53.72% of studies implement systematic validation strategies, indicating methodological immaturity. The most pressing limitation concerns “model generalizability,” stemming from context-specific implementations without transferable frameworks. Finally, based on the existing literature review and in combination Large Language Models (LLMs), the future development trends of HSM are further analyzed to address the current limitations in model construction, validation, and operational efficiency, while establishing a stronger theoretical foundation for method selection and application.