Designing a Blockchain-Based Supply Chain Risk Management Model Using a Genetic Algorithm (Case Study: Dairy Industries of Gilan Province)

Authors

    Fariborz Khoshkar Kisomi Department of Industrial Management, Ra.C., Islamic Azad University, Rasht, Iran.
    Mohammad Ali Enayati Shiraz * Department of Industrial Management, And.C., Islamic Azad University, Andimeshk, Iran. ma.enayati@iau.ac.ir
    Rokhsare Babajafari Esfandabad Department of Management , Ra.C., Islamic Azad University, Rasht, Iran.

Keywords:

Supply Chain Risk Management, Blockchain, Genetic Algorithm, Dairy Products

Abstract

With the expansion of competition and the growing complexity of supply chains—especially in quality-sensitive food industries such as dairy products—the need for innovative approaches to simultaneously manage cost and risk has become increasingly critical. The present study employed a quantitative and applied research method, and data were collected through fieldwork and official statistical sources. The genetic algorithm was implemented with an initial population of 50 chromosomes and 100 generations, incorporating uniform crossover, binary and real-valued mutations, and local search through the genetic algorithm method. In this research, a three-tier supply chain model was designed for the dairy industry of Gilan Province, including suppliers, industrial and traditional production units, and consumer markets, which was optimized using the genetic algorithm. The objective function of the model was to minimize the combined total cost and supply risk with respective weights of 0.7 and 0.3, while the constraints included supplier capacity, production capability of workshops, and full demand satisfaction. Real-world data on capacity, price, transportation cost, and risk indices from three major suppliers were used as model inputs. Simulation of the genetic algorithm with a population of 50 chromosomes and 100 generations showed that the algorithm rapidly reduced costs during the initial generations and gradually converged around generation 80. The final results indicated that the model achieved an optimal total cost of 454,101,315 tomans and an overall risk of 4.87%, with an allocation pattern in which supplier S3 had the largest share, S2 a moderate share, and S1 the smallest share to control risk. This multi-supplier solution effectively balanced cost and risk, and it can be practically applied as a basis for strategic decision-making in the dairy supply chain.

 

 

References

Aein, S., & Noori, T. (2024). Presenting a Conceptual Model and Factors Affecting the Implementation of Blockchain-Based Supply Chain Financing in the Iranian Economy. Quarterly Journal of Monetary and Banking Research, 17(62), 565-595. https://doi.org/10.61186/jmbr.17.62.565

Agnola, T., Ambrosini, L., Beretta, E., & Gremlich, G. (2025). Empowering Global Supply Chains Through Blockchain-Based Platforms: New Evidence from the Coffee Industry. Fintech, 4(1), 3. https://doi.org/10.3390/fintech4010003

Al Aziz, R., Arman, M. H., Karmaker, C. L., Morshed, S. M., Bari, A. M., & Islam, A. R. M. T. (2025). Exploring the challenges to cope with ripple effects in the perishable food supply chain considering recent disruptions: Implications for urban supply chain resilience. Journal of Open Innovation: Technology, Market, and Complexity, 11(1), 100449. https://doi.org/10.1016/j.joitmc.2024.100449

Alkhudary, R., Brusset, X., & Fenies, P. (2020). Blockchain and risk in supply chain management. International Conference on Dynamics in Logistics,

Asghari, H., Eskandari, M., & Moadari, M. (2025). Identifying and Prioritizing Risk Factors in the Logistics of the Supply Chain for Crisis Management with an Integrated Fuzzy Approach. Crisis Prevention and Management Knowledge, 15(1), 7-7. https://doi.org/10.32598/DMKP.15.1.894.1

Bai, C., & Sarkis, J. (2020). A supply chain transparency and sustainability technology appraisal model for blockchain technology. International Journal of Production Research, 58(7), 2142-2162. https://doi.org/10.1080/00207543.2019.1708989

Bednarski, L., Roscoe, S., Blome, C., & Schleper, M. C. (2025). Geopolitical disruptions in global supply chains: a state-of-the-art literature review. Production Planning & Control, 36(4), 536-562. https://www.tandfonline.com/doi/full/10.1080/09537287.2023.2286283

Chang, A., El-Rayes, N., & Shi, J. (2022). Blockchain technology for supply chain management: A comprehensive review. Fintech, 1(2), 191-205. https://doi.org/10.3390/fintech1020015

Chawuthai, R., Murathathunyaluk, S., Amornratthamrong, N., Arunchaipong, R., & Anantpinijwatna, A. (2025). Integration of Genetic Algorithm with Machine Learning for Properties Prediction. Chemical Engineering Transactions,

Chen, Z., Sarkis, J., & Yildizbasi, A. (2025). Digital transformation for safer circular lithium-ion battery supply chains: a blockchain ecosystem-data perspective. International Journal of Production Research, 63(5), 1585-1606. https://doi.org/10.1080/00207543.2024.2381224

Dutta, P., Choi, T. M., Somani, S., & Butala, R. (2020). Blockchain technology in supply chain operations: Applications, challenges and research opportunities. Transportation Research Part E: Logistics and Transportation Review, 142, 102067. https://doi.org/10.1016/j.tre.2020.102067

Fang, C., & Stone, W. Z. (2021). An ecosystem for the dairy logistics supply chain with blockchain technology. 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering,

Hugos, M. H. (2024). Essentials of supply chain management. John Wiley & Sons. https://mrce.in/ebooks/Supply%20Chain%20Management%20Essentials%205th%20Ed.pdf

Jaboob, A. S., Awain, A. M. B., Ali, K. A. M., & Mohammed, A. M. (2024). Introduction to Operation and Supply Chain Management for Entrepreneurship Applying Business Intelligence and Innovation to Entrepreneurship. https://doi.org/10.4018/979-8-3693-1846-1.ch004

Jahaniyan, S., & Kiani, M. (2024). Improving Supply Chain Performance Using Blockchain-Based Smart Contracts: Discrete Event Simulation. Research in Production and Operations Management, 15(4), 59-82. https://doi.org/10.22108/pom.2025.144572.1613

Jha, K. M., Velaga, V., Routhu, K., Sadaram, G., Boppana, S. B., & Katnapally, N. (2025). Transforming Supply Chain Performance Based on Electronic Data Interchange (EDI) Integration: A Detailed Analysis. European Journal of Applied Science, Engineering and Technology, 3(2), 25-40. https://doi.org/10.59324/ejaset.2025.3(2).03

Jiang, Y., Feng, T., & Huang, Y. (2024). Antecedent configurations toward supply chain resilience: the joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, 70(2), 257-284. https://doi.org/10.1002/joom.1282

Khan, T., & Emon, M. M. H. (2025). Supply chain performance in the age of Industry 4.0: evidence from manufacturing sector. Brazilian Journal of Operations & Production Management, 22(1), 2434-2434. https://doi.org/10.14488/BJOPM.2434.2025

Khanna, A., Jain, S., Burgio, A., Bolshev, V., & Panchenko, V. (2022). Blockchain-enabled supply chain platform for Indian dairy industry: Safety and traceability. Foods, 11(17), 2716. https://doi.org/10.3390/foods11172716

Kodym, O., Kubač, L., & Kavka, L. (2020). Risks associated with Logistics 4.0 and their minimization using blockchain. Open Engineering, 10, 74-85. https://doi.org/10.1515/eng-2020-0017

Kumar, R., & Kumar, D. (2023). Blockchain-based smart dairy supply chain: Catching the momentum for digital transformation. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-07-2022-0141

Kumar, R., & Sahoo, S. K. (2025). A Bibliometric Analysis of Agro-Based Industries: Trends and Challenges in Supply Chain Management. Decision Making Advances, 3(1), 200-215. https://doi.org/10.31181/dma31202568

Lin, B., & Zhu, Y. (2025). Supply chain configuration and total factor productivity of renewable energy. Renewable and Sustainable Energy Reviews, 209, 115140. https://doi.org/10.1016/j.rser.2024.115140

Ma, D., Li, K., Qin, H., & Hu, J. (2024). Impacts of blockchain technology on food supply chains with potential food contamination. Electronic Commerce Research and Applications, 64, 101375. https://doi.org/10.1016/j.elerap.2024.101375

Mangla, S. K., Kazançoğlu, Y., Yıldızbaşı, A., Öztürk, C., & Çalık, A. (2022). A conceptual framework for blockchain‐based sustainable supply chain and evaluating implementation barriers: A case of the tea supply chain. Business Strategy and the Environment, 31(8), 3693-3716. https://doi.org/10.1002/bse.3027

Marouti Sharif Abadi, A., Rajabi Pour Meybodi, A., Mohammadi, K., & Mohammadi, L. (2024). Supply Chain Management in the Information Age (Analyzing Research Trends in the Field of Information Flow in Supply Chains). Journal of Information Processing and Management, 39(4), 1477-1505. https://doi.org/10.22034/jipm.2024.2011739.1362

Mohammadi Fateh, A., & Salarnejad, A. A. (2022). The Scope of Blockchain Technology: A Meta-Synthesis Study of Applications, Benefits, Challenges, and Related Technologies. Information Management Sciences and Technologies, 8(1), 245-300. https://doi.org/10.22091/stim.2021.6534.15

Ngo, V. M., Quang, H. T., Hoang, T. G., & Binh, A. D. T. (2024). Sustainability‐related supply chain risks and supply chain performances: The moderating effects of dynamic supply chain management practices. Business Strategy and the Environment, 33(2), 839-857. https://doi.org/10.1002/bse.3512

Orabi, M. M., Emam, O., & Fahmy, H. (2025). Adapting security and decentralized knowledge enhancement in federated learning using blockchain technology: literature review. Journal of Big Data, 12(1), 55. https://doi.org/10.1186/s40537-025-01099-5

Raja, J., Ashish, A., Boianapalli, S., & Rashid, S. Z. (2025). Blockchain Technology in Supply Chain Management Enhancing Transparency and Efficiency. Itm Web of Conferences,

Rani, P., Mishra, A. R., Alshamrani, A. M., Alrasheedi, A. F., & Tirkolaee, E. B. (2025). Picture fuzzy compromise ranking of alternatives using distance-to-ideal-solution approach for selecting blockchain technology platforms in logistics firms. Engineering Applications of Artificial Intelligence, 142, 109896. https://doi.org/10.1016/j.engappai.2024.109896

Rashid, A., Rasheed, R., Ngah, A. H., Pradeepa Jayaratne, M. D. R., Rahi, S., & Tunio, M. N. (2024). Role of information processing and digital supply chain in supply chain resilience through supply chain risk management. Journal of Global Operations and Strategic Sourcing, 17(2), 429-447. https://doi.org/10.1108/JGOSS-12-2023-0106

Rodríguez-Espíndola, O., Alem, D., & Pelegrin Da Silva, L. (2020). A shortage risk mitigation model for multi-agency coordination in logistics planning. Computers & Industrial Engineering, 148, 106676. https://doi.org/10.1016/j.cie.2020.106676

Rogerson, M., & Parry, G. C. (2020). Blockchain: case studies in food supply chain visibility. Supply Chain Management: An International Journal, 25(5), 601-614. https://doi.org/10.1108/SCM-08-2019-0300

Rolf, B., Jackson, I., Müller, M., Lang, S., Reggelin, T., & Ivanov, D. (2023). A review on reinforcement learning algorithms and applications in supply chain management. International Journal of Production Research, 61(20), 7151-7179. https://doi.org/10.1080/00207543.2022.2140221

Romero-Silva, R., & de Leeuw, S. (2021). Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews. Omega, 100, 102388. https://doi.org/10.1016/j.omega.2020.102388

Taqi, R., & Razavi, M. H. (2024). Designing a Risk Management Model for Sustainable Supply Chain in the Football Club Industry of Iran. Sports Management and Development(in press). https://doi.org/10.22124/jsmd.2023.23470.2754

Tiwari, M. K., Bidanda, B., Geunes, J., Fernandes, K., & Dolgui, A. (2024). Supply chain digitisation and management. International Journal of Production Research, 62(8), 2918-2926. https://doi.org/10.1080/00207543.2024.2316476

Tiwari, U. (2020). Application of blockchain in agri-food supply chain. Britain International of Exact Sciences (Bioex) Journal, 2(2), 574-589. https://doi.org/10.33258/bioex.v2i2.233

Vincent, D., Karthika, M., George, J., & Joy, J. (2022). A conception of blockchain platform for milk and dairy products supply chain in an Indian context. Emerging IT/ICT and AI Technologies Affecting Society,

Vu, N., Ghadge, A., & Bourlakis, M. (2023). Blockchain adoption in food supply chains: A review and implementation framework. Production Planning & Control, 34(6), 506-523. https://doi.org/10.1080/09537287.2021.1939902

Ye, X., & Yue, P. (2024). What matters to reshaping consumption patterns in China? Digital inclusion and supply chain. Finance Research Letters, 59, 104804. https://doi.org/10.1016/j.frl.2023.104804

Zaman, A., Tlemsani, I., Matthews, R., & Mohamed Hashim, M. A. (2025). Assessing the potential of blockchain technology for Islamic crypto assets. Competitiveness Review: An International Business Journal, 35(2), 229-250. https://doi.org/10.1108/CR-05-2023-0100

Downloads

Published

2026-01-01

Submitted

2025-06-01

Revised

2025-09-10

Accepted

2025-10-15

Issue

Section

Articles

How to Cite

Khoshkar Kisomi, F. ., Enayati Shiraz, M. A., & Babajafari Esfandabad, R. . (2026). Designing a Blockchain-Based Supply Chain Risk Management Model Using a Genetic Algorithm (Case Study: Dairy Industries of Gilan Province). Journal of Resource Management and Decision Engineering, 1-14. https://www.journalrmde.com/index.php/jrmde/article/view/185

Similar Articles

1-10 of 137

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