Most of the fuzzy supply chain network design problems are single-product models; in addition, the related quality characteristics are ignored in such models. This study tries to increase the efficiency of designed supply chain by considering a multi-product supply chain and giving more attention to effective criteria. In this research, two important problems in supply chain management i.e. supplier selection and supply chain network design are considered simultaneously. Using the fuzzy principal component analysis, a criterion named PCA-score is introduced for considering of the all criteria in an integrated measure. It is used for selecting the supply chain elements. In this study, the parameters have been assumed as trapezoidal fuzzy numbers in order to be closer to the real world situations. A two objectives fuzzy mathematical programming problem is presented and after transforming the fuzzy problem to the equivalent crisp one, LP metric method is used to optimize the crisp problem. Finally, the applicability and efficiency of the model are analyzed using a simulated numerical example.
Bashiri, M., & Sherafati, M. (2013). Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment. Journal of Industrial Engineering Research in Production Systems, 1(1), 25-36.
MLA
M. Bashiri; M. Sherafati. "Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment". Journal of Industrial Engineering Research in Production Systems, 1, 1, 2013, 25-36.
HARVARD
Bashiri, M., Sherafati, M. (2013). 'Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment', Journal of Industrial Engineering Research in Production Systems, 1(1), pp. 25-36.
VANCOUVER
Bashiri, M., Sherafati, M. Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment. Journal of Industrial Engineering Research in Production Systems, 2013; 1(1): 25-36.
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