Objective To enhance the application effectiveness of the decomposition-based optimization method in the large-scale optimization design of ship cabin structures, a constraint progressive relaxation adjustment strategy and a computational resource allocation strategy considering both the contribution of the sub-problem to the objective and the margin of constraints of the sub-problem are proposed.
Methods Constraint progressive relaxation adjustment strategy: Initially, a tightened constraint boundary is given, and then gradually relaxed, until it is recovered to the original constraint boundary, so that all subproblems can be more fully optimized. Computational resource allocation strategy: Optimization computing resources are comprehensively allocated based on the contribution of the subproblem to the objective and the margin of constraints of the subproblem. The two strategies are combined and their coupling effects are analyzed.
Results Compared with the original algorithm, under the same computational resource, the cabin weight is reduced by 10.3% and 7.0% when using the constraint progressive relaxation adjustment strategy and computational resource allocation strategy respectively, the weight is reduced by 22.2% when both strategies are applied simultaneously, relative to the weight obtained by the original optimization method.
Conclusion The proposed strategies are effective and valuable in the decomposition-based large-scale optimization of ship structures.
DownLoad: