Using System Dynamics and Multiple Objective Optimization to Support Policy Analysis for Complex Systems

Abstract

"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."