Journal of Resource Management and Decision Engineering 5 Serial Number 14 2026 02 25 Designing a Blockchain-Based Supply Chain Risk Management Model Using a Genetic Algorithm (Case Study: Dairy Industries of Gilan Province) Designing a Blockchain-Based Supply Chain Risk Management Model Using a Genetic Algorithm (Case Study: Dairy Industries of Gilan Province) 1 14 10.61838/kman.jrmde.185 EN Journal Article 2025 06 01 <p>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.</p> <p> </p> <p> </p> https://journalrmde.com/index.php/jrmde/article/download/185/258