<p>Robotic mixed-model assembly line (RMAL) is challenged to achieve double win for productivity and energy savings in the manufacturing industry. Joint balancing and sequencing is an effective method to enhance the productivity and intelligent collaboration capabilities of RMAL. The energy-saving strategy contributes deeply to reducing energy consumption of RMAL since it is attributed to energy-intensive industry. This study investigates joint balancing and sequencing problem for Type-II RMAL (RMALBSP-II) considering energy consumption. A novel bi-objective model with minimizing the maximum completion time and energy consumption is constructed to achieve joint decision-making and double win objectives for RMALBSP-II. Particularly, production changeover setup is innovatively considered in the model, and robot shutdown strategy is formulated to save energy consumption under the robot’s idle state. To solve the model, a new Multi-objective Discrete Hybrid Cuckoo Search Algorithm (MDHCSA) is explored, and a neighborhood search is used instead of Lévy flight to achieve the search for the discrete optimal solution. Besides, mutation operations within NSGA-II and a new initialization method for task assignment are introduced to improve algorithm performance. Extensive numerical experiments show that the shutdown strategy can save energy and considering the impact of product switching setup can achieve energy saving and efficiency improvement. In addition, the proposed MDHCSA algorithm outperforms other popular multi-objective algorithms.</p>