"This chapter proposes the synthesis of two analytical approaches to support decision making in complex systems. The first, system dynamics, is a proven methodology for modeling and learning in complex systems. The second, multiple objective optimization, is an established approach for exploring the search space of a decision problem, in order to generate optimal solutions to problems with more than one objective. The chapter presents: • An overview of decision making in complex systems; • A summary of the tradition approach to single objective optimization used in system dynamics modelling; • An explanation of multiple objective optimization; • An illustrative case study1, based on the Beer Game, which integrates multiple objective optimization with system dynamics, and provides a practical way for decision makers to fully explore policy alternatives in a complex system micro-world."
CITATION STYLE
Duggan, J. (2007). Using System Dynamics and Multiple Objective Optimization to Support Policy Analysis for Complex Systems. In Complex Decision Making (pp. 59–81). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-73665-3_4
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