The cooling supply chain, due to its high energy consumption and refrigerant emissions, has high levels of greenhouse gas emissions and is one of the largest carbon emitters. In the cold supply chain, products should be stored at low and near or below freezing points. F
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The cooling supply chain, due to its high energy consumption and refrigerant emissions, has high levels of greenhouse gas emissions and is one of the largest carbon emitters. In the cold supply chain, products should be stored at low and near or below freezing points. For this purpose, refrigerated warehouses and refrigerated trucks are essential. Therefore, this research aims to design a linear multi-objective decision-making model for supply chain management Which aims to reduce the overall supply chain cost, including the cost of capacity, transportation, inventory as well as costs associated with the effects of global warming due to greenhouse gas emissions. To analyze the research problem, a mathematical model for optimizing the supply chain has been designed and genetic algorithm has been used to solve this problem. The results of the first function test indicate that the model is high in the number of customers, and when the distributor's number is equal to the number of producers, the best one is possible. The second function analysis concludes that reducing the restoration time of the facility is effective in minimizing the first function, reducing costs and reducing greenhouse gas emissions. Therefore, according to the stated contents and the results obtained in this research, it can be pointed out that by optimizing the vehicles and also the proper use of the optimal number of means of transport, it can be expected that the pollution and proliferation of gases The greenhouse is at least possible.
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