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A Hybrid Genetic Algorithm-Ratio DEA Approach for Assessing Sustainable Efficiency in Two-Echelon Supply Chains

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  • Mohammad Reza Mozaffari

    (Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran)

  • Sahar Ostovan

    (Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran)

  • Peter Fernandes Wanke

    (COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, Rio de Janeiro 21949-900, Brazil)

Abstract

Measuring sustainable efficiency is a wide research topic that has gained increased relevance over the course of the years, particularly in the field of supply chain management. In this paper, novel Data Envelopment Analysis—ratio data (DEA-R) models are used to assess sustainable efficiency in two-echelon supply chains based on endogenous factors. Genetic algorithms are employed to determine optimal productive weights for each echelon and the overall supply chain by taking into account the hidden correlation structures among them as expressed in non-linear multi-objective functions. A case study on 20 firefighting stations is presented to illustrate the approach proposed and its accuracy for decision-making, as long as the issues of pseudo inefficiency and over estimation of efficiency scores are mitigated. Results indicate that the method proposed is capable of reducing efficiency estimation biases due to endogenous sustainable factors by yielding overall scores lower than or equal to the product of the efficiencies of the individual stages.

Suggested Citation

  • Mohammad Reza Mozaffari & Sahar Ostovan & Peter Fernandes Wanke, 2020. "A Hybrid Genetic Algorithm-Ratio DEA Approach for Assessing Sustainable Efficiency in Two-Echelon Supply Chains," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8075-:d:422023
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    References listed on IDEAS

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    1. Liu, W.B. & Zhang, D.Q. & Meng, W. & Li, X.X. & Xu, F., 2011. "A study of DEA models without explicit inputs," Omega, Elsevier, vol. 39(5), pages 472-480, October.
    2. Eskandarpour, Majid & Dejax, Pierre & Miemczyk, Joe & Péton, Olivier, 2015. "Sustainable supply chain network design: An optimization-oriented review," Omega, Elsevier, vol. 54(C), pages 11-32.
    3. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2014. "Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 324-338.
    4. Floridi, Matteo & Pagni, Simone & Falorni, Simone & Luzzati, Tommaso, 2011. "An exercise in composite indicators construction: Assessing the sustainability of Italian regions," Ecological Economics, Elsevier, vol. 70(8), pages 1440-1447, June.
    5. Olesen, Ole Bent & Petersen, Niels Christian & Podinovski, Victor V., 2015. "Efficiency analysis with ratio measures," European Journal of Operational Research, Elsevier, vol. 245(2), pages 446-462.
    6. Olesen, Ole Bent & Petersen, Niels Christian & Podinovski, Victor V., 2017. "Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs," European Journal of Operational Research, Elsevier, vol. 261(2), pages 640-655.
    7. Liu, Qian & Zheng, Lucy, 2016. "Assessing the economic performance of an environmental sustainable supply chain in reducing environmental externalitiesAuthor-Name: Ding, Huiping," European Journal of Operational Research, Elsevier, vol. 255(2), pages 463-480.
    8. Singh, Akshit & Shukla, Nagesh & Mishra, Nishikant, 2018. "Social media data analytics to improve supply chain management in food industries," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 398-415.
    9. Yoo, Seung Ho & Cheong, Taesu, 2018. "Quality improvement incentive strategies in a supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 331-342.
    10. Zhong, Yuanguang & Shu, Jia & Xie, Wei & Zhou, Yong-Wu, 2018. "Optimal trade credit and replenishment policies for supply chain network design," Omega, Elsevier, vol. 81(C), pages 26-37.
    11. Majid Azadi & Seyed Mostafa Mirhedayatian & Reza Farzipoor Saen & Mahshid Hatamzad & Ehsan Momeni, 2017. "Green supplier selection: a novel fuzzy double frontier data envelopment analysis model to deal with undesirable outputs and dual-role factors," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 25(2), pages 160-181.
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