Traditional heavy industries that are energy-intensive have much potential for energy saving and carbon emission reduction. Focusing on the production scheduling of steelmaking continuous casting, this study aims to propose a twin transformation strategy and investigate the impact on sustainable indicators while considering resource efficiency and productivity. Continuous casting is energy-intensive and the bottleneck for steelmaking. The batching and sequencing of the charges are crucial for energy resource management. This study developed a hybrid genetic algorithm that integrated charge batching decisions to minimize makespan and the total weighted tardiness for continuous casting while minimizing energy consumption for a circular supply chain. An empirical study is conducted to estimate the validity of this approach under various scenarios in real settings. The results have shown practical viability of the developed solution that has been implemented in this case company, while the developed solutions can be effectively employed in other industries for sustainability.