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

This paper aims to investigate the multi-objective optimization problem of typical container ship structures.

First, a ship structural component library to discretize the optimization variables was established. Next, an improved particle swarm optimization-simulated annealing (IPSO-SA) algorithm 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, an MOPSO-SA algorithm for multi-objective optimization was developed.

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. The IPSO-SA resulted in a 26.05% reduction in weight, while the MOPSO-SA approach resulted in a 14.11% decrease in structural weight, and a 12.95% reduction in the vertical center of gravity.

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