Simulation optimisation of a sustainable copper mining closed-loop supply chain

References

• Ahluwalia, R. K., Wang, X., Papadias, D. D., & Star, A. G. (2022). Performance and total cost of ownership of a fuel cell hybrid mining truck. Energies, 16(1), 286. https://doi.org/10.3390/en16010286
   Web of Science ®Google Scholar
• Aloui, A., Hamani, N., & Delahoche, L. (2021). Designing a resilient and sustainable logistics network under epidemic disruptions and demand uncertainty. Sustainability, 13(24), 14053. https://doi.org/10.3390/su132414053
   Web of Science ®Google Scholar
• Azadeh, A., & Vafa Arani, H. (2016). Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach. Renewable Energy, 93, 383–403. https://doi.org/10.1016/j.renene.2016.02.070
   Web of Science ®Google Scholar
• Barbosa, C., Malarranha, C., Azevedo, A., Carvalho, A., & Barbosa-Póvoa, A. (2023). A hybrid simulation approach applied in sustainability performance assessment in make-to-order supply chains: The case of a commercial aircraft manufacturer. Journal of Simulation, 17(1), 32–57. https://doi.org/10.1080/17477778.2021.1931500
   Web of Science ®Google Scholar
• Becerra, P., Mula, J., & Sanchis, R. (2021). Green supply chain quantitative models for sustainable inventory management: A review. Journal of Cleaner Production, 328, 129544. https://doi.org/10.1016/j.jclepro.2021.129544
   Web of Science ®Google Scholar
• Becerra, P., Mula, J., & Sanchis, R. (2023). Optimising location, inventory and transportation in a sustainable closed-loop supply chain. International Journal of Production Research, Article in press. https://doi.org/10.1080/00207543.2023.2197515
   Google Scholar
• Bostel, N., Dejax, P., & Lu, Z. (2005). The design, planning, and optimization of reverse logistics networks. In A. Langevin & D. Riopel (Eds.), Logistics systems: Design and optimization (pp. 171–212). Springer. https://doi.org/10.1007/0-387-24977-X_6
   Google Scholar
• Buschiazzo, M., Mula, J., & Campuzano-Bolarin, F. (2020). Simulation optimization for the inventory management of healthcare supplies. International Journal of Simulation Modelling, 19(2), 255–266. https://doi.org/10.2507/IJSIMM19-2-514
   Web of Science ®Google Scholar
• Calmon, A. P., & Graves, S. C. (2017). Inventory management in a consumer electronics closed-loop supply chain. Manufacturing & Service Operations Management, 19(4), 568–585. https://doi.org/10.1287/msom.2017.0622
   Google Scholar
• Campuzano, F., & Mula, J. (2011). Supply chain simulation. Springer. https://doi.org/10.1007/978-0-85729-719-8
   Google Scholar
• Campuzano-Bolarín, F., Mula, J., Díaz-Madroñero, M., & Legaz-Aparicio, Á-G. (2020). A rolling horizon simulation approach for managing demand with lead time variability. International Journal of Production Research, 58(12), 3800–3820. https://doi.org/10.1080/00207543.2019.1634849
   Web of Science ®Google Scholar
• Campuzano-Bolarín, F., Mula, J., & Peidro, D. (2013). An extension to fuzzy estimations and system dynamics for improving supply chains. International Journal of Production Research, 51(10), 3156–3166. https://doi.org/10.1080/00207543.2012.760854
   Web of Science ®Google Scholar
• Chakraborty, S., Adhikari, S., & Ganguli, R. (2021). The role of surrogate models in the development of digital twins of dynamic systems. Applied Mathematical Modelling, 90, 662–681. https://doi.org/10.1016/j.apm.2020.09.037
   Web of Science ®Google Scholar
• Chen, W., Kucukyazici, B., Verter, V., & Jesús Sáenz, M. (2015). Supply chain design for unlocking the value of remanufacturing under uncertainty. European Journal of Operational Research, 247(3), 804–819. https://doi.org/10.1016/j.ejor.2015.06.062
   Web of Science ®Google Scholar
• Deng, S., Li, Y., Zhou, T., & Cao, Y. (2014). Study on recyclable reserve logistics network optimization based on e-commerce. Proceedings - 2014 International Conference on Management of e-Commerce and e-Government, ICMeCG 2014 (pp. 337–340). Shanghai, China, October 31 - November 2. https://doi.org/10.1109/ICMeCG.2014.75
   Google Scholar
• Díaz-Madroñero, M., Mula, J., Jiménez, M., & Peidro, D. (2017). A rolling horizon approach for material requirement planning under fuzzy lead times. International Journal of Production Research, 55(8), 2197–2211. https://doi.org/10.1080/00207543.2016.1223382
   Web of Science ®Google Scholar
• Dolgui, A., Ivanov, D., & Sokolov, B. (2018). Ripple effect in the supply chain: An analysis and recent literature. International Journal of Production Research, 56(1–2), 414–430. https://doi.org/10.1080/00207543.2017.1387680
   Web of Science ®Google Scholar
• Ekren, B. Y., Mangla, S. K., Turhanlar, E. E., Kazancoglu, Y., & Li, G. (2021). Lateral inventory share-based models for IoT-enabled E-commerce sustainable food supply networks. Computers & Operations Research, 130, 105237. https://doi.org/10.1016/j.cor.2021.105237
   Web of Science ®Google Scholar
• Esteso, A., Mula, J., Campuzano-Bolarín, F., Diaz, M. A., & Ortiz, A. (2019). Simulation to reallocate supply to committed orders under shortage. International Journal of Production Research, 57(5), 1552–1570. https://doi.org/10.1080/00207543.2018.1493239
   Web of Science ®Google Scholar
• Freile, A. J., Mula, J., & Campuzano-Bolarin, F. (2020). Integrating inventory and transport capacity planning in a food supply chain. International Journal of Simulation Modelling, 19(3), 434–445. https://doi.org/10.2507/IJSIMM19-3-523
   Web of Science ®Google Scholar
• Ghadge, A., Er, M., Ivanov, D., & Chaudhuri, A. (2022). Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A system dynamics approach. International Journal of Production Research, 60(20), 6173–6186. https://doi.org/10.1080/00207543.2021.1987547
   Web of Science ®Google Scholar
• Ivanov, D., Sokolov, B., & Dolgui, A. (2014). The ripple effect in supply chains: Trade-off ‘efficiency-flexibility-resilience’ in disruption management. International Journal of Production Research, 52(7), 2154–2172. https://doi.org/10.1080/00207543.2013.858836
   Web of Science ®Google Scholar
• Jindal, A., Sangwan, K. S., & Saxena, S. (2015). Network design and optimization for multi-product, multi-time, multiechelon closed-loop supply chain under uncertainty. Procedia CIRP, 29, 656–661. https://doi.org/10.1016/j.procir.2015.01.024
   Google Scholar
• Kuo, T. C. (2011). The study of production and inventory policy of manufacturing/remanufacturing environment in a closed-loop supply chain. International Journal of Sustainable Engineering, 4(4), 323–329. https://doi.org/10.1080/19397038.2011.593008
   Google Scholar
• Liu, Y., Zhao, R., Wu, K.-J., Huang, T., Chiu, A., & Cai, C. (2018). A hybrid of multi-objective optimization and system dynamics simulation for straw-to-electricity supply chain management under the belt and road initiatives. Sustainability, 10(3), 868. https://doi.org/10.3390/su10030868
   Web of Science ®Google Scholar
• Llaguno, A., Mula, J., & Campuzano-Bolarin, F. (2022). State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains. International Journal of Production Research, 60(6), 2044–2066. https://doi.org/10.1080/00207543.2021.1877842
   Web of Science ®Google Scholar
• Mohammadi, M. A., Sayadi, A. R., Khoshfarman, M., & Husseinzadeh Kashan, A. (2022). A systems dynamics simulation model of a steel supply chain-case study. Resources Policy, 77, 102690. https://doi.org/10.1016/j.resourpol.2022.102690
   Web of Science ®Google Scholar
• Motevalli-Taher, F., Paydar, M. M., & Emami, S. (2020). Wheat sustainable supply chain network design with forecasted demand by simulation. Computers and Electronics in Agriculture, 178, 105763. https://doi.org/10.1016/j.compag.2020.105763
   Web of Science ®Google Scholar
• Rebs, T., Brandenburg, M., & Seuring, S. (2019). System dynamics modeling for sustainable supply chain management: A literature review and systems thinking approach. Journal of Cleaner Production, 208, 1265–1280. https://doi.org/10.1016/j.jclepro.2018.10.100
   Web of Science ®Google Scholar
• Rezapour, S., Farahani, R. Z., Fahimnia, B., Govindan, K., & Mansouri, Y. (2015). Competitive closed-loop supply chain network design with price-dependent demands. Journal of Cleaner Production, 93, 251–272. https://doi.org/10.1016/j.jclepro.2014.12.095
   Web of Science ®Google Scholar
• Sharif, A. M. (2005). Can systems dynamics be effective in modelling dynamic business systems? Business Process Management Journal, 11(5), 612–615. https://doi.org/10.1108/14637150510619911
   Google Scholar
• Sterman, J. (2000). Business dynamics: Systems thinking and modeling for a complex world. Irwin/McGraw-Hill. https://books.google.es/books?id=CCKCQgAACAAJ
   Google Scholar
• Sudarto, S., Takahashi, K., & Morikawa, K. (2017). Efficient flexible long-term capacity planning for optimal sustainability dimensions performance of reverse logistics social responsibility: A system dynamics approach. International Journal of Production Economics, 184, 179–192. https://doi.org/10.1016/j.ijpe.2016.12.013
   Web of Science ®Google Scholar
• Tako, A. A., & Robinson, S. (2012). The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decision Support Systems, 52(4), 802–815. https://doi.org/10.1016/j.dss.2011.11.015
   Web of Science ®Google Scholar
• Tighazoui, A., Turki, S., Sauvey, C., & Sauer, N. (2019). Optimal design of a manufacturing-remanufacturing-transport system within a reverse logistics chain. International Journal of Advanced Manufacturing Technology, 101(5–8), 1773–1791. https://doi.org/10.1007/s00170-018-2945-2
   Web of Science ®Google Scholar