<p>This study presents a novel risk-based robust mixed-integer linear programming model for configuring a complex cement supply chain network under carbon emission policies (CEPs). In addition to the non-deterministic model solved with the robust approach, its corresponding deterministic model is also solved and the results are compared. In the models, critical dimensions of the cement industry, including inventory and shortages, are mathematically examined. Other important features of the industry, including the large number of suppliers of different materials, the production of diverse products with different processing flows, and diverse transportation methods appropriate to different types of cement and market climates, are also considered in the models. A scenario-based conditional value-at-risk approach is used to deal with the inherent uncertainty of cement demand in the uncertain counterpart of the model. The results demonstrate the effectiveness of the robust approach for the optimal configuration of the integrated cement inventory-production system and its inbound-outbound logistics. Analyzing the results establishes widespread trade-offs between the parameters. In particular, the model suggests the highest level of risk-taking for a profit-sensitive DM to maximize her/his profit. It may push the robustness-sensitive DM toward more conservatism by accepting lower profits. Besides, an emission-sensitive DM is recommended to implement both the carbon-cap-and-trade and carbon tax under carbon cap-and-trade regulation policies.</p> Graphical abstract <p></p>