Despite the widespread adoption of robots across various industries, service-oriented sectors such as hospitality continue to face significant limitations in deploying robots due to the inherently unstructured nature of service tasks. Customers still tend to prefer interactions with human employees, while exceptional situations that fall outside predefined procedures frequently arise in practice. Therefore, rather than pursuing the complete replacement of human employees, there is a growing need to establish a systematic and interdependent human–robot cooperation framework. This study proposes an optimal operational system for interdependent human–robot cooperation in restaurant environments and redefines robots not merely as substitutes for human labor but as complementary partners. This study developed a multi-objective optimization model that simultaneously minimizes total operating costs, including robot subscription fees and employee labor costs, as well as employees’ physical workload, while satisfying predefined customer satisfaction targets. In the proposed framework, repetitive and physically demanding transportation tasks are assigned to robots, whereas personalized face-to-face services are performed by human employees. Furthermore, realistic operational constraints are mathematically incorporated, including employee break requirements mandated by labor regulations, robot battery charging requirements, and the negative impact of accumulated employee fatigue on service quality. To address operational problems of varying scales, this study implements a staged solution approach that combines mathematical optimization techniques for obtaining baseline optimal solutions, metaheuristic algorithms for large-scale operational problems, and reinforcement learning methods to capture uncertainty in real-time environments. This study presents a leading framework at the intersection of service operations management and ergonomics and provides practical insights for sustainable technology integration in service industries.