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Sustainable supply chains: An integrated modeling approach under uncertainty

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  • Mota, Bruna
  • Gomes, Maria Isabel
  • Carvalho, Ana
  • Barbosa-Povoa, Ana Paula

Abstract

This work presents ToBLoOM – Triple Bottom Line Optimization Modeling, a decision support tool for the design and planning of sustainable supply chains. It consists of a multi-objective mixed integer linear programming model which integrates several interconnected decisions: facility location and capacity determination; supplier selection and purchase levels definition; technology selection and allocation; transportation network definition including both unimodal and intermodal options; supply planning; product recovery and remanufacturing. The three pillars of sustainability are addressed as objective functions: economic, through Net Present Value; environmental through the Life Cycle Analysis methodology ReCiPe; and social through a developed GDP-based metric. Uncertainty is considered using a stochastic ToBloOM. This applied to a case of a European based company with markets in Europe and South America. This work contributes to the literature by building on several identified research gaps such as the need for an integrated approach that allows simultaneous assessment of different interacting supply chain decisions, the need to explicitly assess the environmental impact in closed-loop supply chains, the need to assess the impact of supply chains on society, and the need for a multi-objective tool that includes all the three pillars of sustainability. Strategies towards a more sustainable supply chain are also derived from this work.

Suggested Citation

  • Mota, Bruna & Gomes, Maria Isabel & Carvalho, Ana & Barbosa-Povoa, Ana Paula, 2018. "Sustainable supply chains: An integrated modeling approach under uncertainty," Omega, Elsevier, vol. 77(C), pages 32-57.
  • Handle: RePEc:eee:jomega:v:77:y:2018:i:c:p:32-57
    DOI: 10.1016/j.omega.2017.05.006
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    Cited by:

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    3. Tautenhain, Camila P.S. & Barbosa-Povoa, Ana Paula & Mota, Bruna & Nascimento, Mariá C.V., 2021. "An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem," European Journal of Operational Research, Elsevier, vol. 294(1), pages 70-90.
    4. Xiaoyan Li & Xuedong Liang & Zhi Li, 2023. "The Strategy of Strengthening Efficiency and Environmental Performance of Product Changeover in the Multiproduct Production System," SAGE Open, , vol. 13(3), pages 21582440231, September.
    5. Shoufeng Ji & Pengyun Zhao & Tingting Ji, 2023. "A Hybrid Optimization Method for Sustainable and Flexible Design of Supply–Production–Distribution Network in the Physical Internet," Sustainability, MDPI, vol. 15(7), pages 1-34, April.
    6. Omid Abdolazimi & Farzad Bahrami & Davood Shishebori & Majid Alimohammadi Ardakani, 2022. "A multi-objective closed-loop supply chain network design problem under parameter uncertainty: comparison of exact methods," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 10768-10802, September.
    7. Jonkman, Jochem & Barbosa-Póvoa, Ana P. & Bloemhof, Jacqueline M., 2019. "Integrating harvesting decisions in the design of agro-food supply chains," European Journal of Operational Research, Elsevier, vol. 276(1), pages 247-258.
    8. Vijayta Fulzele & Ravi Shankar, 2023. "Performance measurement of sustainable freight transportation: a consensus model and FERA approach," Annals of Operations Research, Springer, vol. 324(1), pages 501-542, May.
    9. Aijun Liu & Yan Zhang & Senhao Luo & Jie Miao, 2020. "Dual-Channel Global Closed-Loop Supply Chain Network Optimization Based on Random Demand and Recovery Rate," IJERPH, MDPI, vol. 17(23), pages 1-32, November.
    10. Carlos A. Moreno-Camacho & Jairo R. Montoya-Torres & Anicia Jaegler, 2023. "Sustainable supply chain network design: a study of the Colombian dairy sector," Annals of Operations Research, Springer, vol. 324(1), pages 573-599, May.
    11. Luttiely Santos Oliveira & Ricardo Luiz Machado, 2021. "Application of optimization methods in the closed-loop supply chain: a literature review," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 357-400, February.
    12. Xiaoyu Yang & Xiaopeng Guo & Kun Yang, 2021. "Redesigning the Municipal Solid Waste Supply Chain Considering the Classified Collection and Disposal: A Case Study of Incinerable Waste in Beijing," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
    13. Dominguez, Roberto & Cannella, Salvatore & Ponte, Borja & Framinan, Jose M., 2020. "On the dynamics of closed-loop supply chains under remanufacturing lead time variability," Omega, Elsevier, vol. 97(C).
    14. Ahmad, Firoz & Alnowibet, Khalid A. & Alrasheedi, Adel F. & Adhami, Ahmad Yusuf, 2022. "A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    15. Chandra, Dheeraj & Kumar, Dinesh, 2021. "Evaluating the effect of key performance indicators of vaccine supply chain on sustainable development of mission indradhanush: A structural equation modeling approach," Omega, Elsevier, vol. 101(C).
    16. Pablo Flores-Siguenza & Jose Antonio Marmolejo-Saucedo & Joaquina Niembro-Garcia, 2023. "Robust Optimization Model for Sustainable Supply Chain Design Integrating LCA," Sustainability, MDPI, vol. 15(19), pages 1-16, September.
    17. Xifeng Tang & Jiantao Wu & Rui Li, 2020. "Efficient Allocation of Customers to Facilities in the Multi-Objective Sustainable Location Problem," Sustainability, MDPI, vol. 12(18), pages 1-12, September.
    18. Baptista, Susana & Barbosa-Póvoa, Ana Paula & Escudero, Laureano F. & Gomes, Maria Isabel & Pizarro, Celeste, 2019. "On risk management of a two-stage stochastic mixed 0–1 model for the closed-loop supply chain design problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 91-107.
    19. Shen, Jiayu, 2020. "An uncertain sustainable supply chain network," Applied Mathematics and Computation, Elsevier, vol. 378(C).

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