Research on Workstation Planning of Spacecraft Pulsating Assembly Lines Based on Improved Genetic Algorithm

The article focuses on the production mode of a satellite pulsating assembly line and conducts research on workstation planning. An optimal planning model for the pulsation assembly line is constructed based on the number of workstations, with the objectives of minimizing production cycle time and average idle time. A new coding method based on cursor address is proposed in genetic algorithm to divide virtual parallel workstations. An elite strategy is added to the selection operation to improve the survival rate of the optimal individual. Furthermore, adaptive crossover and mutation strategies based on Sigmoid function are designed to enhance the algorithm’s ability to search for optimal solutions. The improved genetic algorithm (IGA) is utilized for multi-objective optimization solving of the model, resulting in an optimal workstation planning scheme. Through examples from a satellite pulsating assembly line, this study verifies the feasibility of the algorithm while improving balance rate and production efficiency of satellite assembly lines.