Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEEM.2009.5373149
Title: System dynamics simulation and optimization with fuzzy logic
Authors: Ng, T.S. 
Khirudeen, M.I.B.
Halim, T.
Chia, S.Y.
Keywords: Fuzzy logic
Genetic algorithm
Simulation
System dynamics
Table function
Issue Date: 2009
Source: Ng, T.S., Khirudeen, M.I.B., Halim, T., Chia, S.Y. (2009). System dynamics simulation and optimization with fuzzy logic. IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management : 2114-2118. ScholarBank@NUS Repository. https://doi.org/10.1109/IEEM.2009.5373149
Abstract: This paper presents a novel and practical approach for integrating simulation and optimization of system dynamics (SD) models using Matlab and Simulink. The Matlab platform allows much freedom in customizing and implementing global search techniques such as genetic algorithms (GA) and artificial intelligence constructs like fuzzy logic. The Simulink platform allows complex nonlinear dynamic models to be specified rapidly. In this work we demonstrate how to combine the GA parameter search, fuzzy logic expert input and SD modeling to arrive at better strategies for decision making. This approach to optimization is illustrated using the classical market growth-model and produces very competitive good results. ©2009 IEEE.
Source Title: IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management
URI: http://scholarbank.nus.edu.sg/handle/10635/72415
ISBN: 9781424448708
DOI: 10.1109/IEEM.2009.5373149
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