طراحي زنجيره تامين موادغذايي درشرايط رقابتي و با در نظر گرفتن ريسك‌هاي اختلال

Designing the food supply chain in competitive condition an‎d considering the risks of disruption

مديريت

The aim of this research is to present an optimization model for the design an‎d decision-making of a perishable-product supply chain network, with an emphasis on the concept of supply chain resilience an‎d considering a hierarchical decision-making structure among supply chain members. In this study, the interaction among the main actors of the supply chain is modeled as a Stackelberg game, whereby the manufacturer, as the leader of the game, influences the decisions of other supply chain members by setting wholesale pricing policies. In the proposed model, in addition to pricing decisions, production, procurement, an‎d distribution decisions are considered simultaneously, an‎d the effects of disruptions an‎d product perishability on the network performance an‎d its resilience are examined. The proposed model is first formulated as a mathematical model an‎d then solved using the Particle Swarm Optimization (PSO) metaheuristic algorithm in the MATLAB environment. To eva‎luate the accuracy of the solutions, the results obtained from the proposed algorithm are compared with the exact solution of the model in GAMS software. In addition, to analyze the behavior of the model an‎d assess its sensitivity, a sensitivity analysis is performed on some key parameters such as budget, prices, an‎d disruption intensity. The results of the study show that the hierarchical decision-making structure an‎d pricing policies play an important role in the profitability of the supply chain network. Moreover, increasing the level of disruption an‎d product perishability can significantly reduce the total profit of the system, while proper network design an‎d the adoption of coordinated management policies can help enhance the resilience of the supply chain against disruptions. The findings of this research can assist managers in making effective decisions regarding pricing, production planning, an‎d the design of resilient supply chain networks.

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