The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Fuzzy System Dynamics: An Application to Supply Chain Management
Abstract
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.
Related Content
Pawan Kumar, Mukul Bhatnagar, Sanjay Taneja.
© 2024.
26 pages.
|
Kapil Kumar Aggarwal, Atul Sharma, Rumit Kaur, Girish Lakhera.
© 2024.
19 pages.
|
Mohammad Kashif, Puneet Kumar, Sachin Ghai, Satish Kumar.
© 2024.
15 pages.
|
Manjit Kour.
© 2024.
13 pages.
|
Sanjay Taneja, Reepu.
© 2024.
19 pages.
|
Jaspreet Kaur, Ercan Ozen.
© 2024.
28 pages.
|
Hayet Kaddachi, Naceur Benzina.
© 2024.
25 pages.
|
|
|