An optimization design method for submarine cabins based on intelligent algorithms

Submarine compartment layout design is a multi-objective optimization problem, which needs to consider the mutual position, passage relationship, comfort, convenience, and other aspects between compartments. Based on the characteristics of submarine living cabin layouts, this paper introduces a fuzzy evaluation method to comprehensively analyze the functional adjacency and personnel circulation relationships between compartments. Moreover, combined with emergency evacuation requirements, the study established a double layer cabin layout optimization model and proposed a multi-population genetic algorithm for optimizing the layout of submarine living cabins. Simulation experiments were conducted using MATLAB software to validate the algorithm's effectiveness. A comparison was made between the multi-population genetic algorithm and the standard genetic algorithm. The results verify the feasibility of the proposed design method and its ability to effectively address the submarine compartment layout optimization problem, thereby improving the efficiency of compartment layout optimization design. • Proposing multi-population genetic algorithms for submarine cabin layout optimization design. • The study introduced fuzzy processing for analyzing cabin relationships and defining a multi-objective optimization model. • Comparative analysis between MPGA and SGA demonstrated the superior performance of MPGA. • The proposed method provides feasible layout solutions, reducing workload and improving efficiency for design personnel. • The method proposed in this study provides a basis and reference for the layout design of other submarine cabin segments.