Green design of regional wheat supply chains under uncertainty

Document Type : Article

Authors

Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran

Abstract

This study presents a fuzzy mathematical programming model to optimize regional wheat hub center in Iran with the aim of achieving sustainable self-sufficiency, swap and export of wheat to neighboring countries. The proposed model is developed for a 10-year planning horizon with real-world assumptions under uncertainty. By the proposed model, the optimal decisions are made on the amount of wheat cultivation areas in different provinces, capacity of silos, amount of import, swap and export of wheat, transportation mode and storage amount of wheat in different periods. Two objective functions including economic and environmental goals are optimized by the proposed model. The proposed model is examined under uncertainty conditions and the possibilistic programming approach is used to deal with the uncertainty of parameters. Finally, the presented model is validated through investigating a real case study in Iran. The results show the efficiency of the model for making optimal strategic and tactical decisions in wheat supply chains.

Keywords

References

References
1. http://en.gtc-portal.com/.
2. Statistics, A., Ministry of agriculture, Islamic Republic of Iran (2008).
3. Djuric, I. and Götz, L. “Export restrictions – Do consumers really benefit? The wheat-to-bread supply chain in Serbia”, Food Policy, 63, pp. 112-123 (2016). doi.org/10.1016/j.foodpol.2016.07.002.
4. Gholamian, M.R. and Taghanzadeh, A.H. “Integrated network design of wheat supply chain: A real case of Iran”, Computers and Electronics in Agriculture, 140, pp. 139–147 (2017). doi.org/10.1016/j.compag.2017.05.038.
5. Hosseini-Motlagh, S.M., Samani, M.R.G., and Abbasi Saadi, F. “A novel hybrid approach for synchronized development of sustainability and resiliency in the wheat network”, Computers and Electronics in Agriculture, 168, 105095 (2020). doi.org/10.1016/j.compag.2019.105095.
6. Pourmohammadi, F., Teimoury, E., and Gholamian, M. “A fuzzy chance-constrained programming model for integrated planning of the wheat supply chain considering wheat quality and sleep period: a case study”, Scientia Iranica, 29(5), pp. 2593-2609 (2022). DOI: 10.24200/sci.2020.53772.3404.
7. Trisna, T., Marimin, M., Arkeman, Y., et al. “Fuzzy multi-objective optimization for wheat flour supply chain considering raw material substitution”, International Journal of Industrial Engineering and Management, 11(3), pp. 180-191 (2021). doi.org/10.24867/IJIEM-2020-3-263.
8. Naderi, B., Govindan, K., and Soleimani, H. “A Benders decomposition approach for a real case supply chain network design with capacity acquisition and transporter planning: wheat distribution network”, Annals of Operations Research, 291(1), pp. 685-705 (2020). doi.org/10.1007/s10479-019-03137-x.
9. Motevalli-Taher, F., Paydar, M.M., and Emami, S. “Wheat sustainable supply chain network design with forecasted demand by simulation”, Computers and Electronics in Agriculture, 178, 105763 (2020). doi.org/10.1016/j.compag.2020.105763.
10. Stanco, M., Nazzaro, C., Lerro, M., et al. “Sustainable collective innovation in the agri-food value chain: The case of the “Aureo” wheat supply chain”, Sustainability, 12(14), 5642 (2020). doi.org/10.3390/su12145642.
11. Dossa, A.A., Gough, A., Batista, L., et al. “Diffusion of circular economy practices in the UK wheat food supply chain”, International Journal of Logistics Research and Applications, 25(3), pp. 328-347 (2022). doi.org/10.1080/13675567.2020.1837759.
12. Deng, L., Zhang, H., Wang, C., et al. “Improving the sustainability of the wheat supply chain through multi-stakeholder engagement”, Journal of Cleaner Production, 321, 128837 (2021). doi.org/10.1016/j.jclepro.2021.128837.
13. Govindan, K., Fattahi, M., and Keyvanshokooh, E. “Supply chain network design under uncertainty: A comprehensive review and future research directions”, European Journal of Operational Research, 263(1), pp. 108-141 (2017). doi.org/10.1016/j.ejor.2017.04.009.
14. Anderson, E. and Monjardino, M. “Contract design in agriculture supply chains with random yield”, European Journal of Operational Research, 277(3), pp. 1072-1082 (2019). doi.org/10.1016/j.ejor.2019.03.041.
15. Ghelichi, Z., Saidi-Mehrabad, M., and Pishvaee, M.S. “A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: A case study”, Energy, 156, pp. 661-687 (2018). doi.org/10.1016/j.energy.2018.05.103.
16. Babazadeh, R. “Application of fuzzy optimization to bioenergy supply chain planning under Epistemic Uncertainty: A new approach”, Industrial & Engineering Chemistry Research, 58, pp. 6519−6536 (2019). doi.org/10.1021/acs.iecr.8b05617.
17. Babazadeh, R., Razmi, J., Pishvaee, M.S., et al. “A sustainable second-generation biodiesel supply chain network design problem under risk”, Omega, 66, pp. 258-277 (2017). doi.org/10.1016/j.omega.2015.12.010.
18. Mousavi, A.P., Ghaderi, S.F., Azadeh, A., et al. “Hybrid multiobjective robust possibilistic programming approach to a sustainable bioethanol supply chain network design”, Industrial & Engineering Chemistry Research, 57, pp. 15066-15083 (2018). doi.org/10.1021/acs.iecr.8b02869.
19. Mavrotas, G. “Effective implementation of the ε-constraint method in multi-objective Mathematical programming problems”, Applied Mathematics and Computation, 213(2), pp. 455–465 (2009). doi.org/10.1016/j.amc.2009.03.037.
20. Sahebjamnia, N., Torabi, S.A., and Mansouri, S.A. “Integrated business continuity and disaster recovery planning: Towards organizational resiliency”, European Journal of Operational Research, 242(1), pp. 261–273 (2015). doi.org/10.1016/j.ejor.2014.09.055.
21. Ehrgott, M., Multicriteria Optimization, Springer, Berlin (2005). doi.org/10.1007/3-540-27659-9.
22. Aghaei, J., Amjady, N., and Shayanfar, H.A. “Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method”, Applied Soft Computing, 11, pp. 3846–3858 (2011). doi.org/10.1016/j.asoc.2011.02.022.
Scientia Iranica
Volume 31, Issue 22
Transactions on Industrial Engineering (E)
November and December 2024
Pages 2166-2180

Files

History

  • Receive Date: 12 July 2020
  • Revise Date: 13 April 2022
  • Accept Date: 29 May 2022

Share

How to cite

Statistics