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Integrating supplier selection, lot sizing and facility location decisions under a TBL approach: a case study
Triple bottom line (TBL) is one of the well-known frameworks for measuring the sustainability of a system in which environmental and social aspects are also considered together with the economic aspect. In this study, we consider the integrated supplier selection, lot sizing and facility location de...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860377/ https://www.ncbi.nlm.nih.gov/pubmed/35221790 http://dx.doi.org/10.1007/s00500-022-06866-7 |
Sumario: | Triple bottom line (TBL) is one of the well-known frameworks for measuring the sustainability of a system in which environmental and social aspects are also considered together with the economic aspect. In this study, we consider the integrated supplier selection, lot sizing and facility location decisions and propose a two-phase decision framework based on TBL approach. In the first phase of the study, we use a trapezoidal type-2 fuzzy AHP algorithm for the initial evaluation of the suppliers based on various economic, environmental and social criteria, whereas in the second phase of the study, we propose a two-stage stochastic programming model for the integrated supplier selection, lot sizing and facility location decisions under supply and demand uncertainties. We also present a real-life case study to test the proposed decision framework. Computational results, on one hand, show the applicability of the proposed decision framework on real-life cases and, on the other hand, bring significant managerial insights. Particularly, we observe that all three pillars (economic, environmental and social) of sustainability are in conflict with each other and thus being both environmentally and socially responsible is much more costlier than being solely environmentally or socially responsible. Moreover, we observe that ignoring the uncertainties in the system may yield to higher costs and impractical results. |
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