Designing a Food Security Supply Chain for Sustainable Oil Production Using a Non-Dominated Sorting Genetic Algorithm (NSGA-II) Approach

Authors

  • Mostafa Farokhiani * Department of Industrial Engineering, Imam Hossein University, Tehran, Iran. https://orcid.org/0009-0009-5078-5321
  • Soheila Tabashir Department of English, Yasuj University. Yasuj, Iran.
  • Hossein Ali Hassan Pour Department of Industrial Engineering, Imam Hossein University, Tehran, Iran.
  • Hossein Ghaffari Touran Department of Industrial Engineering, Imam Hossein University, Tehran, Iran.

https://doi.org/10.48313/scodm.v3i1.51

Abstract

Governments' key priorities include increasing food security and quality. Food security is influenced by food availability, financial ability to get food (affordability or accessibility), quality (utility), and sustainability. In light of food security concerns and the contractual approach, the current study presents and resolves a model for establishing supply chain networks for basic food products. The supply chain network investigated in this study includes two types of consumers, sunflower canola oil producer and oilseed suppliers. This study evaluated prior studies to identify food security dimensions and factors impacting a food security chain. Then, for field study, two questionnaires were constructed. The factors of food security and associated criteria were approved by research specialists who used the original questionnaire. The resulting questionnaire is then used to identify the most critical factors influencing food security in the supply chain being studied. The mathematical model of the supply chain that promotes domestic production and uses a contractual method was created. The "comprehensive criterion (LP-metric)" method was utilized to solve the problem in small dimensions. The multi-objective mathematics presented in this study is of the NP-hard type and the metaheuristic algorithm of Non- Dominated Sorting Genetic Algorithm (NSGA-II) was used to solve the model in large dimensions. In order to validate, the results of this algorithm were compared with the exact solution results (comprehensive benchmark method). The results of the studies indicate the appropriate performance of the metaheuristic algorithm. Finally, a sensitivity analysis was performed to examine the effect of parameters on the objective functions.

Keywords:

Network design, Supply chain, Food security, Sustainability of food security, Factors affecting food security

References

  1. [1] Westengen, O. T., & Banik, D. (2016). The state of food security: From availability, access and rights to food systems approaches. In Forum for development studies (Vol. 43, No. 1, pp. 113-134). https://doi.org/10.1080/08039410.2015.1134644

  2. [2] Deng, X., Han, Z., Xie, W., Wang, G., & Fan, Z. (2024). Risk evaluation of the grain supply chain in China. International journal of logistics research and applications, 27(1), 83–102. https://doi.org/10.1080/13675567.2021.2009450

  3. [3] Oriekhoe, O. I., Adisa, O., & Ilugbusi, B. S. (2024). Climate change and food supply chain economics: a comprehensive analysis of impacts, adaptations, and sustainability. International journal of applied research in social sciences, 6(3), 267–278. https://doi.org/10.51594/ijarss.v6i3.885

  4. [4] Belhadi, A., Kamble, S., Subramanian, N., Singh, R. K., & Venkatesh, M. (2024). Digital capabilities to manage agri-food supply chain uncertainties and build supply chain resilience during compounding geopolitical disruptions. International journal of operations & production management, 44(11), 1914–1950. https://doi.org/10.1108/IJOPM-11-2022-0737

  5. [5] Kozielec, A., Piecuch, J., Daniek, K., & Luty, L. (2024). Challenges to food security in the Middle East and North Africa in the context of the Russia--Ukraine Conflict. Agriculture, 14(1), 155. https://doi.org/10.3390/agriculture14010155

  6. [6] Alam, M. F. Bin, Tushar, S. R., Ahmed, T., Karmaker, C. L., Bari, A. B. M. M., de Jesus Pacheco, D. A., … Islam, A. R. M. T. (2024). Analysis of the enablers to deal with the ripple effect in food grain supply chains under disruption: implications for food security and sustainability. International journal of production economics, 270, 109179. https://doi.org/10.1016/j.ijpe.2024.109179

  7. [7] Amhamed, A., Genidi, N., Abotaleb, A., Sodiq, A., Abdullatif, Y., Hushari, M., & Al-Kuwari, M. (2023). Food security strategy to enhance food self-sufficiency and overcome international food supply chain crisis: the state of Qatar as a case study. Green technology, resilience, and sustainability, 3(1), 3. https://doi.org/10.1007/s44173-023-00012-8%0A%0A

  8. [8] Barakat, S., Cochrane, L., & Vasekha, I. (2023). The humanitarian-development-peace nexus for global food security: Responding to the climate crisis, conflict, and supply chain disruptions. International journal of disaster risk reduction, 98, 104106. https://doi.org/10.1016/j.ijdrr.2023.104106

  9. [9] Sagi, V., & Gokarn, S. (2023). Determinants of reduction of food loss and waste in Indian agri-food supply chains for ensuring food security: A multi-stakeholder perspective. Waste management & research, 41(3), 575–584. https://doi.org/10.1177/0734242X221126421

  10. [10] Tonelli, D., Rosa, L., Gabrielli, P., Parente, A., & Contino, F. (2024). Cost-competitive decentralized ammonia fertilizer production can increase food security. Nature food, 5(6), 469–479. https://doi.org/10.1038/s43016-024-00979-y%0A%0A

  11. [11] Varzakas, T., & Smaoui, S. (2024). Global food security and sustainability issues: the road to 2030 from nutrition and sustainable healthy diets to food systems change. Foods, 13(2), 306. https://doi.org/10.3390/foods13020306

  12. [12] Cunningham, S. A., Shaikh, N. I., Datar, A., Chernishkin, A. E., & Patil, S. S. (2021). Food subsidies, nutrition transition, and dietary patterns in a remote Indian district. Global food security, 29, 100506. https://doi.org/10.1016/j.gfs.2021.100506

  13. [13] Hashem, N. M., González-Bulnes, A., & Rodriguez-Morales, A. J. (2020). Animal welfare and livestock supply chain sustainability under the COVID-19 outbreak: An overview. Frontiers in veterinary science, 7, 582528. https://doi.org/10.3389/fvets.2020.582528

  14. [14] Nhemachena, C., Nhamo, L., Matchaya, G., Nhemachena, C. R., Muchara, B., Karuaihe, S. T., & Mpandeli, S. (2020). Climate change impacts on water and agriculture sectors in Southern Africa: Threats and opportunities for sustainable development. Water, 12(10), 2673. https://doi.org/10.3390/w12102673

  15. [15] Sundram, P., & Brennan, C. S. (2024). Triumphs, trials and tomorrow in food security: an ASEAN outlook. International journal of food science and technology, 59(4), 2079–2087. https://doi.org/10.1111/ijfs.16899

  16. [16] López, M. M., Vera Andreo, J., Plà Aragonés, L. M., & Recalde-Ramírez, J. L. (2026). Design of a mathematical model to optimize farmer food security and promote rural development in Paraguay. Annals of Operations Research, 358(2), 667-704. https://doi.org/10.1007/s10479-024-06199-8%0A%0A

  17. [17] Kazemi, M. J., & Samouei, P. (2024). A new bi-level mathematical model for government-farmer interaction regarding food security and environmental damages of pesticides and fertilizers: Case study of rice supply chain in Iran. Computers and electronics in agriculture, 219, 108771. https://doi.org/10.1016/j.compag.2024.108771

  18. [18] Khan, Y., Ashraf, S., & Shah, M. (2024). Determinants of food security through statistical and fuzzy mathematical synergy. Environment, development and sustainability, 26(6), 14981–14999. https://doi.org/10.1007/s10668-023-03231-y%0A%0A

  19. [19] Hamidoğlu, A. (2024). A game-theoretical approach on the construction of a novel agri-food supply chain model supported by the government. Expert systems with applications, 237, 121353. https://doi.org/10.1016/j.eswa.2023.121353

  20. [20] Esteso, A., Alemany, M. M. E., & Ortiz, A. (2024). Sustainable agri-food supply chain planning through multi-objective optimisation. Journal of decision systems, 33(4), 808–832. https://doi.org/10.1080/12460125.2023.2180138

  21. [21] Abbas, H., Zhao, L., Gong, X., & Faiz, N. (2023). The perishable products case to achieve sustainable food quality and safety goals implementing on-field sustainable supply chain model. Socio-economic planning sciences, 87, 101562. https://doi.org/10.1016/j.seps.2023.101562

  22. [22] Daneshvar, A., Radfar, R., Ghasemi, P., Bayanati, M., & Pourghader Chobar, A. (2023). Design of an optimal robust possibilistic model in the distribution chain network of agricultural products with high perishability under uncertainty. Sustainability, 15(15), 11669. https://doi.org/10.3390/su151511669

  23. [23] Gholian-Jouybari, F., Hashemi-Amiri, O., Mosallanezhad, B., & Hajiaghaei-Keshteli, M. (2023). Metaheuristic algorithms for a sustainable agri-food supply chain considering marketing practices under uncertainty. Expert systems with applications, 213, 118880. https://doi.org/10.1016/j.eswa.2022.118880

  24. [24] Azab, R., Mahmoud, R. S., Elbehery, R., & Gheith, M. (2023). A bi-objective mixed-integer linear programming model for a sustainable agro-food supply chain with product perishability and environmental considerations. Logistics, 7(3), 46. https://doi.org/10.3390/logistics7030046

  25. [25] Rahbari, M., Khamseh, A. A., & Mohammadi, M. (2023). A novel multi-objective robust fuzzy stochastic programming model for sustainable agri-food supply chain: case study from an emerging economy. Environmental science and pollution research, 30(25), 67398–67442. https://doi.org/10.1007/s11356-023-26305-w%0A%0A

  26. [26] Fasihi, M., Tavakkoli-Moghaddam, R., Najafi, S. E., Hajiaghaei-Keshteli, M., & others. (2021). Developing a bi-objective mathematical model to design the fish closed-loop supply chain. International journal of engineering, 34(5), 1257-1268. https://doi.org/10.5829/ije.2021.34.05b.19

  27. [27] Esteso, A., Alemany, M. M. E., & Ortiz, Á. (2021). Impact of product perishability on agri-food supply chains design. Applied mathematical modelling, 96, 20–38. https://doi.org/10.1016/j.apm.2021.02.027

  28. [28] Yang, Q., Xiong, L., Li, Y., Chen, Q., Yu, Y., & Wang, J. (2022). Contract coordination of fresh agri-product supply chain under O2O model. Sustainability, 14(14), 8771. https://doi.org/10.3390/su14148771

  29. [29] Hou, J., Wu, L., & Hou, B. (2020). Risk attitude, contract arrangements and enforcement in food safety governance: a China’s agri-food supply chain scenario. International journal of environmental research and public health, 17(8), 2733. https://doi.org/10.3390/ijerph17082733

  30. [30] Patidar, R., & Agrawal, S. (2020). A mathematical model formulation to design a traditional Indian agri-fresh food supply chain: A case study problem. Benchmarking: an international journal, 27(8), 2341–2363. https://doi.org/10.1108/BIJ-01-2020-0013

  31. [31] Poonia, V., Kulshrestha, R., & Sangwan, K. S. (2024). A comparative study of $varepsilon$-constraint, LP-metric, and weighted sum multi-objective optimization methods in a circular economy. Procedia cirp, 122, 294–299. https://doi.org/10.1016/j.procir.2024.01.043

  32. [32] Hassanpour, H. A., Taheri, M. R., & Rezanezhad, R. (2020). Designing a food supply chain network under uncertainty and solving by multi-objective metaheuristics. International journal of supply and operations management, 7(4), 350–372. https://doi.org/10.22034/ijsom.2020.4.5

Published

2026-02-22

How to Cite

Farokhiani, M. ., Tabashir, S., Hassan Pour, H. A. ., & Ghaffari Touran, H. . (2026). Designing a Food Security Supply Chain for Sustainable Oil Production Using a Non-Dominated Sorting Genetic Algorithm (NSGA-II) Approach. Supply Chain and Operations Decision Making, 3(1), 46-62. https://doi.org/10.48313/scodm.v3i1.51

Similar Articles

1-10 of 31

You may also start an advanced similarity search for this article.