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Fuzzy System Dynamics: An Application to Supply Chain Management

Fuzzy System Dynamics: An Application to Supply Chain Management
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Author(s): Michael Mutingi (Namibia University of Science and Technology, Namibia) and Charles Mbohwa (University of Johannesburg, South Africa)
Copyright: 2014
Pages: 24
Source title: Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
Source Author(s)/Editor(s): Pandian M. Vasant (Petronas University of Technology, Malaysia)
DOI: 10.4018/978-1-4666-4450-2.ch008


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In the presence of fuzzy or linguistic and dynamic variables, dynamic modeling of real-world systems is a challenge to many decision makers. In such environments with fuzzy time-dependent variables, the right decisions and the impacts of possible actions are not precisely known. The presence of linguistic variables in a dynamic environment is a serious cause for concern to most practicing decision makers. For instance, in a demand-driven supply chain, demand information is inherently imprecise, leading to unwanted fluctuations throughout the supply chain. This chapter integrates, from a systems perspective, fuzzy logic and system dynamics paradigms to model a typical supply chain in a fuzzy environment. Based on a set of performance indices defined to evaluate supply chain behavior, results from comparative simulation experiments show the utility of the fuzzy system dynamics paradigm: (1) the approach provides a real-world picture of a fuzzy dynamic supply chain, (2) expert opinion can be captured into a dynamic simulation model with ease, (3) the fuzzy dynamic policies yield better supply chain performance, and (4) “what-if analysis” show the robustness of the fuzzy dynamic policies even in turbulent demand situations. Managerial insights and practical evaluations are provided.

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