A structural optimization method for container ships based on an improved particle swarm-simulated annealing algorithm

Objective To investigate the multi-objective optimization problem of typical container ship structures.

Method This paper first established a ship structural component library to discretize the optimization variables. Next, an improved PSO-SA algorithm (IPSO-SA) with dynamically adjusted optimization parameters was proposed. This method facilitates the 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 developed.

Results Taking the parallel middle body structure optimization of a container ship as an example, the parametric model of the structural components was constructed with the established component library, and the proposed optimization algorithm was applied. This approach resulted in a 26.05% reduction in weight, a 14.11% decrease in structural weight, and a 12.95% reduction in the vertical center of gravity.

Conclusion The research not only improved the economic efficiency of the original design but also significantly enhanced the stability of the container ship.