Data Envelopment Analyses
Majid Yarahmadi; Saeedeh Sakiniya
Abstract
Purpose: This paper presents an intelligent method for applying Data Envelopment Analysis (DEA) to design a sustainable supply chain.Methodology: In the proposed method, for defuzzification of the ERM model, we used the -cutting technique. Then, to measure the productivity in the presence of environmental ...
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Purpose: This paper presents an intelligent method for applying Data Envelopment Analysis (DEA) to design a sustainable supply chain.Methodology: In the proposed method, for defuzzification of the ERM model, we used the -cutting technique. Then, to measure the productivity in the presence of environmental uncertainty via different -levels, a genetic algorithm is implemented to find an optimal -cutting. Finally, an intelligent DEA model for ranking the supplier companies via optimal value is designed.Findings: This paper presents a new fuzzy DEA model based on a Genetic Algorithm for evaluating the productivity of suppliers in a sustainable supply chain.Originality/Value: In the proposed method, since the -cut obtained from the Genetic Algorithm is optimal, there is no longer a need to calculate the efficiency for different α-cuts through trial and error. Therefore, the proposed method's advantage is that it offers a more sustainable ranking in addition to increasing productivity for each supplier. The example presented in this article demonstrates the method's superiority and advantages.