Review of research on ship cabin spatial layout optimization

In the field of ship design, the spatial layout of compartments is not only crucial for enhancing navigation safety and operational efficiency but also serves as an important guarantee for crew comfort and overall ship performance. This paper aims to construct a multi-dimensional evaluation system for compartment layout optimization, systematically review relevant optimization algorithms, analyze current technical bottlenecks, and propose future research directions, thereby providing theoretical and technical support for the intelligent design of ship compartments. First, a multi-dimensional evaluation system for the optimization of ship compartment spatial layout is summarized and proposed. This system comprehensively considers various factors such as functional correlation, absolute position, human activities, environment, and weight distribution, providing clear objectives and directions for the selection and design of subsequent optimization algorithms. Taking into account the differences in functional requirements and design focuses of different types of ships, as well as the availability of data in practical applications, users can flexibly select applicable indicator combinations from this evaluation system based on specific scenarios to conduct targeted scientific evaluations. Then, a systematic review is conducted of the important algorithms proposed by researchers in recent years in the field of ship compartment layout optimization, including but not limited to genetic algorithm, improved tabu search algorithm, gravitational search algorithm, integer programming method, and group motion simulation driven method. The research achievements of these optimization algorithms in solving high-quality spatial layouts are summarized and organized. Next, a support relationship table between optimization methods and evaluation indicators is constructed, and the mainstream optimization methods are systematically reviewed and compared from multiple dimensions such as algorithm principles, solution efficiency, multi-objective processing capability, and engineering usability, aiming to evaluate the applicability of optimization methods in ship compartment layout optimization tasks. At the same time, for complex scenarios of multi-deck, the differences between single-deck and multi-deck spatial layout optimization are compared, examples of multi-deck spatial layout optimization are summarized, and shortcomings are analyzed. Furthermore, the rationality and scientific nature of the constructed evaluation system are verified through case studies of multi-deck. The study finds that although various algorithms have made significant progress in the field of ship compartment spatial layout optimization, there are still many limitations, such as generally not considering problems from the micro-execution level, and difficulty in efficiently modeling multi-deck layouts. Finally, this paper proposes prospects for future research directions from multiple perspectives, including high-quality ship deck compartment layout datasets, new intelligent optimization algorithms, and human-in-the-loop deep reinforcement learning frameworks.