@article{LI2026, 
author = {Hongwei LI and Changjie YING and Guan GUAN},
title = {A structural optimization method for container ships based on an improved particle swarm-simulated annealing algorithm},
year = {2026},
journal = {Chinese Journal of Ship Research},
volume = {21},
number = {5},
pages = {184-192},
keywords = {ship structural optimization, simulated annealing algorithm, particle swarm optimization algorithm, multi-objective optimization, ship structural component library},
url = {https://www.sciopen.com/article/10.19693/j.issn.1673-3185.04540},
doi = {10.19693/j.issn.1673-3185.04540},
abstract = {ObjectiveThis paper aims to investigate the multi-objective optimization problem of typical container ship structures. Method 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. Results 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.ConclusionThe research not only improved the economic efficiency of the original design but also significantly enhanced the stability of the container ship.}
}