Title :
System dynamics simulation and optimization with fuzzy logic
Author :
Ng, T.S. ; Khirudeen, M. I B ; Halim, T. ; Chia, S.Y.
Author_Institution :
Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore, Singapore
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.
Keywords :
digital simulation; fuzzy logic; genetic algorithms; large-scale systems; mathematics computing; GA parameter search; Matlab; Simulink; fuzzy logic expert input; genetic algorithms; global search techniques; market growth model; system dynamics models optimization; system dynamics simulation; Artificial intelligence; Computational modeling; Delay; Feedback loop; Fuzzy logic; Genetic algorithms; Marketing and sales; Mathematical model; Nonlinear dynamical systems; Systems engineering and theory; System dynamics; fuzzy logic; genetic algorithm; simulation; table function;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
DOI :
10.1109/IEEM.2009.5373149
