Abstract: To address the integrated optimization of layout and scheduling in fiber optic gyroscope assembly workshops, this paper incorporates the principle of lean logistics into the solution process. A mixed-integer programming model is developed with the objectives of minimizing the makespan, lean logistics distances and workstation layout rationality. Based on the specific problem features, an adaptive non-dominated sorting genetic algorithm III (NSGA-III) is designed to solve this problem. A crossover operator based on independent evolution is designed to better preserve high-quality encoding segments representing lean solutions without detours, reflows, or production waiting, thereby enhancing the exploratory capability of the algorithm. A "substitution-elimination" strategy is proposed to repair infeasible individuals generated during crossover. To reduce the waste of detours in logistics routes, a swap mutation operator is designed based on the lean logistics principle. Finally, an instance analysis is conducted on the assembly task of fiber optic gyroscope products in an enterprise to verify the effectiveness of the proposed approach.