Metaheuristic optimization methods for calibration of system dynamics models

Juan Felipe Parra, Patricia Jaramillo and Santiago Arango-Aramburo

Journal of Simulation, 2018, vol. 12, issue 2, 190-209

Abstract: System Dynamics models require calibration as part of the validation process. The available software tools only include one of the methods available for this end. But, the nature of this process requires sensitivity not only within a method, but with different methods. This study tests the effects of four optimisers (Genetic Algorithms, Simulated Annealing, Powell’s Algorithm, and a hybrid algorithm) in the calibration process of two system dynamics models. It was not possible to find an overall best optimizer algorithm due to three factors: model complexity, parameters for calibration and the measures (objective function) to evaluate the accuracy of the optimiser. Therefore, the choice of optimization method has an influence on the fit, limits, and representativeness of the model. More research is needed.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2018.1467850 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjsmxx:v:12:y:2018:i:2:p:190-209

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1080/17477778.2018.1467850

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

More articles in Journal of Simulation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().