Objective In order to reduce the dependence of ship conceptual design on design experience and mother ship data while improving design efficiency and quality, a main hull subdivision intelligent optimization method is proposed.

Method First, the mutual influence relationships between ship cabin equipment are analyzed and a topological representation model and automatic identification method for such relationships are proposed. Based on design experience and statistical rules, a favorable impact topological objective function and geometric objective function for the space utilization rate are constructed, and a probability damage constraint model is proposed according to the design specifications. Based on the theory of membrane computing, a multi-objective optimization solution is realized, forming a set of intelligent optimization methods for the main hull subdivision. A main hull subdivision optimization design test is then carried out on the research ship "Dayang".

Results The Pareto front solution set obtained from the optimization has good diversity. Compared with the mother type subdivision scheme, the optimal subdivision scheme has a favorable impact increase of 18.9583 and reduces the number of watertight compartments by one.

Conclusion The test results indicate that this method is rational and feasible.