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.
| Original language | English |
|---|---|
| Title of host publication | Handbook of Research on Novel Soft Computing Intelligent Algorithms |
| Subtitle of host publication | Theory and Practical Applications |
| Publisher | IGI Global |
| Pages | 234-257 |
| Number of pages | 24 |
| Volume | 1-2 |
| ISBN (Electronic) | 9781466644519 |
| ISBN (Print) | 1466644508, 9781466644502 |
| DOIs | |
| Publication status | Published - 31 Aug 2013 |
ASJC Scopus subject areas
- General Computer Science