Presenting a Dairy Supply Chain Risk Management Model Based on Blockchain Technology Using the Simulated Annealing Metaheuristic Algorithm
Keywords:
Supply chain risk management, dairy industries, blockchain, simulated refrigeration algorithm, multi, objective optimization, GuilanAbstract
Objective: The objective of this study was to design and validate a blockchain-based dairy supply chain risk management model using the simulated annealing algorithm for simultaneous optimization of cost and risk.
Methodology: This applied study employed a descriptive–analytical simulation approach. The research population consisted of dairy supply chain actors organized within a three-tier structure including suppliers, processing plants, and market demand nodes. Operational data such as production capacity, procurement and transportation costs, market demand, and risk indicators were collected from industry records. The proposed model incorporated binary and quantitative decision variables, stochastic demand modeled through Poisson distribution, and parametric disruption risks. A multi-objective optimization framework was solved using the simulated annealing metaheuristic, and algorithm performance was evaluated through convergence behavior and sensitivity analysis.
Findings: The results demonstrated that simulated annealing successfully minimized total supply chain cost and risk simultaneously while achieving stable convergence toward optimal solutions. Sensitivity analysis confirmed robustness of the model under variations in risk weighting, demand fluctuations, and cooling parameters. The optimal solution adopted a multi-supplier allocation strategy that improved operational flexibility and balanced risk exposure across the supply chain network.
Conclusion: Integrating blockchain technology with simulated annealing provides an effective framework for dairy supply chain risk management, enhancing transparency, resilience, and strategic decision-making in multi-tier supply systems.
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