Using white‐box nonlinear optimization methods in system dynamics policy improvement

Vierhaus, Ingmar; Fügenschuh, Armin; Gottwald, Robert; Grösser, Stefan (2018). Using white‐box nonlinear optimization methods in system dynamics policy improvement Sytem Dynamics Review, 2(33), pp. 138-168. Wiley 10.1002/sdr.1583

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We present a new strategy for the direct optimization of the values of policy functions. This approach is particularly well suited to model actors with a global perspective on the system and relies heavily on modern mathematical white‐box optimization methods. We demonstrate our strategy on two classical models: market growth and World2. Each model is first transformed into an optimization problem by defining how the actor can influence the models' dynamics and by choosing objective functions to measure improvements. To improve comparability between different runs, we also introduce a comparison measure for possible interventions. We solve the optimization problems, discuss the resulting policies and compare them to the existing results from the literature. In particular, we present a run of the World2 model which significantly improves the published “towards a global equilibrium” run with equal cost of intervention.

Item Type:	Journal Article (Original Article)
Division/Institute:	School of Engineering and Computer Science > Institute for Data Applications and Security (IDAS) School of Engineering and Computer Science School of Engineering and Computer Science > Institute for ICT-based Management (ICTM)
Name:	Vierhaus, Ingmar; Fügenschuh, Armin; Gottwald, Robert and Grösser, Stefan0000-0003-3412-2711
ISSN:	1099-1727
Publisher:	Wiley
Language:	English
Submitter:	Service Account
Date Deposited:	29 Jan 2020 11:35
Last Modified:	18 Dec 2020 13:28
Publisher DOI:	10.1002/sdr.1583
ARBOR DOI:	10.24451/arbor.7164
URI:	https://arbor.bfh.ch/id/eprint/7164