A Structural Optimization Method for Container Ships Based on Improved Particle Swarm-Simulated Annealing Algorithm

To investigate the multi-objective optimization problem of typical container ship structures, this paper first established a ship structural component library to achieve the discretization of optimization variables. Secondly, an improved PSO-SA algorithm (IPSO-SA) with dynamically adjusted optimization parameters was proposed. This method enables rapid identification of the global optimal solution for single-objective optimization problems. Then, by introducing Pareto dominance, a MOPSO-SA algorithm for multi-objective optimization was proposed. Taking the parallel middle body structure optimization of a container ship as an example, the parametric model of the structural components was constructed using the established component library, and the proposed optimization algorithm was applied. This not only achieved a 26.051% reduction in weight but also realized a 14.111% reduction in structural weight while lowering the vertical center of gravity by 12.951%. The research results not only improved the economic efficiency of the original design but also significantly enhanced the stability of the container ship.