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 are proposed that consider both the contribution of the sub-problem to the objective and the margin of constraints of the sub-problem.
Methods Constraint progressive relaxation adjustment strategy: initially, a tightened constraint boundary is given and then gradually relaxed until it recovers to the original constraint boundary, enabling all sub-problems to be more fully optimized. Computational resource allocation strategy: optimization computing resources are comprehensively allocated based on the contribution of the sub-problem to the objective and the margin of constraints of the sub-problem. The two strategies are then combined and their coupling effects analyzed.
Results Compared with the original algorithm, under the same computational resources, 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, and 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 possess value for the decomposition-based large-scale optimization of ship structures.
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