Analysis of dynamic models by optimization

Decision‐makers use system dynamics models to understand how model structure causes problematic behaviors, and how the structure should be changed to improve performance. However, understanding problem behavior and designing policies can be complicated without analytical tools. Existing methods focu...

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Bibliographic Details
Published in:System dynamics review 2024-01, Vol.40 (1), p.n/a
Main Authors: Moxnes, Erling, Naumov, Sergey
Format: Article
Language:English
Subjects:
Decision analysis
Differential equations
Dynamic models
Dynamic structural analysis
Feedback loops
Optimization
Policies
System dynamics
Systems design
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Summary:Decision‐makers use system dynamics models to understand how model structure causes problematic behaviors, and how the structure should be changed to improve performance. However, understanding problem behavior and designing policies can be complicated without analytical tools. Existing methods focus on feedback loops that drive dynamic behavior. We propose a new method, Analysis of Dynamic Models by Optimization (ADMO), which focuses on understanding the causes of well‐defined problems and on guiding system and policy design. Unlike existing methods, ADMO can evaluate the influence of exogenous variables and nonlinearities, leading to new understandings of endogenous behavior and providing insights for policy design. ADMO can be employed with any model, including differential equation, agent‐based, discrete event, or hybrid, requiring minimal effort. Two cases demonstrate the application of ADMO to analyze problems and improve both system design and policies. © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
ISSN:0883-7066
1099-1727
DOI:10.1002/sdr.1747