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Equation-based policy optimization for agent-oriented system dynamics models

ARAN - Access to Research at NUI Galway

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dc.contributor.author Duggan, Jim en
dc.date.accessioned 2010-05-27T10:45:36Z en
dc.date.available 2010-05-27T10:45:36Z en
dc.date.issued 2008-01-01 en
dc.identifier.citation Duggan, J. (2008). Equation-based policy optimization for agent-oriented system dynamics models. 'System Dynamics Review', 24(1), 97-118. en
dc.identifier.issn 0883-7066 en
dc.identifier.uri http://hdl.handle.net/10379/1131 en
dc.description.abstract Within system dynamics, optimization has played an important role in identifying the best range of parameter values for policies in any given model. Optimal solutions focus on discovering the best combination of model parameters, within a fixed policy equation structure, that maximize or minimize a payoff function. This paper presents a new optimization approach for system dynamics. It enables decision makers to vary policy equation structures during the optimization process. The resulting optimization approach - based on genetic algorithms - can explore the search space in order to discover the best combination of parameters and equation-based strategies for a given system dynamics problem. The approach is best suited to the class of system dynamics problems that are agent-based, and the work is evaluated using a case study based on the four-agent beer game en
dc.format application/pdf en
dc.language.iso en en
dc.publisher Wiley Blackwell en
dc.subject.lcsh Information technology en
dc.title Equation-based policy optimization for agent-oriented system dynamics models en
dc.type Article en
dc.local.publishedsource http://www3.interscience.wiley.com/journal/119163362/abstract en
dc.description.peer-reviewed peer-reviewed en

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