Supply Chain Management and Its Importance in the Era of Globalization with the Presentation of a Mathematical Model

Abstract

This study examines the role of futures contracts in financial risk management within the supply chain under the volatile economic conditions of Iran. In light of challenges arising from price and currency fluctuations, financial instruments such as futures contracts are analyzed as a strategy to mitigate risk and enhance stability across the supply chain. The research introduces a mathematical model based on a hybrid of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), integrating them into a Hybrid Genetic-Particle algorithm (HGP), to account for critical factors such as risk aversion levels, demand variability, and price volatility. The dataset utilized in the study was extracted from the Iran Khodro Company. The results demonstrate that the HGP algorithm outperforms both GA and PSO in terms of accuracy for risk prediction and factor loading, exhibiting a lower margin of error in modeling long-term risks and price fluctuations. Moreover, the sensitivity analysis of futures contracts reveals that these instruments can be effectively employed for risk hedging under conditions of economic instability. This study offers a practical framework and proposes strategies to improve supply chain management within domestic industries, emphasizing the need to strengthen financial infrastructure and establish transparent regulatory frameworks. Based on the findings, it is recommended that the HGP model be applied in key industries such as automotive manufacturing and petrochemicals to evaluate its operational efficiency. Additionally, the development of artificial intelligence software for risk monitoring, enhancement of decision-making processes, and the formulation of standardized methodologies for risk assessment and contract valuation by regulatory bodies can significantly contribute to the reinforcement of financial infrastructure.