<![CDATA[Abstract. One of the most important recent topics that has been considered by researchers, is the fate of industrial products and goods with the end customer which has led to the creation of the concept of reverse supply chain. Reverse supply chain management includes all the processes of collecting products used by the customer, recycling, reproducing (repairing) and disposing of some unusable parts. Considering the importance of using reverse logistics in waste collection and also the importance of the fourth industrial revolution, the present study has been formed with the aim of Innovation in reverse supply chain model through industry 4.0 revolutions. In this research, a mathematical model for the reverse supply chain of municipal waste in conditions of uncertainty based on the pattern of the Industrial Revolution 4 is presented. This supply chain is the levels of distribution centers, customers, collection centers, recycling centers and destruction centers. Innovations of this research present and solve the mathematical model of the reverse supply chain of municipal waste recycling with the approach of Industrial Revolution Four, considering the dimensions of sustainability in the reverse supply chain of municipal waste recycling with the approach of Industry 4 Revolution, considering the location-routing phase in The reverse supply chain for municipal waste recycling is four with the Industrial Revolution approach. The understudy model is multi-objective and its objectives include minimizing transportation costs and environmental impacts and maximizing the amount of demand responded to the customer. Determining and identifying the dimensions of the Industrial Revolution Model 4, weighting the dimensions of the Industrial Revolution Model 4 in the sustainable reverse supply chain of municipal waste recycling, designing an integrated model of the sustainable reverse supply chain of municipal waste recycling based on the weight dimensions of the Industrial Revolution Model 4 and designing Implementation of meta-heuristic algorithms to solve the model]]>
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