Loading...

Robust-fuzzy model for supplier selection under uncertainty: an application to the automobile industry

Rabieh, M ; Sharif University of Technology | 2018

448 Viewed
  1. Type of Document: Article
  2. DOI: 10.24200/sci.2017.4456
  3. Publisher: Sharif University of Technology , 2018
  4. Abstract:
  5. This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and especially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which could be applicable to multiple uncertainties conditions. Thus, in our approach, the half-length of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluate the results by simulation technique and compare values of objective function under different scenarios. © 2018 Sharif University of Technology. All rights reserved
  6. Keywords:
  7. Robust-fuzzy model ; Automotive industry ; Fuzzy systems ; Optimization ; Auto industry ; Fuzzy programming ; Robust fuzzy ; Robust optimization ; Supplier selection ; Uncertainty ; Membership functions ; Automobile industry ; Data set ; Fuzzy mathematics ; Innovation ; Linear programing ; Methodology ; Numerical model ; Uncertainty analysis
  8. Source: Scientia Iranica ; Volume 25, Issue 4 , 2018 , Pages 2297-2311 ; 10263098 (ISSN)
  9. URL: http://scientiairanica.sharif.edu/article_4456.html