船舶舱室空间布局优化研究综述

Review of research on ship cabin spatial layout optimization

  • 摘要: 在船舶设计领域,舱室空间布局不仅是提升航行安全性与运营效率的关键,也是船员舒适度和船舶整体性能的重要保障。本文旨在构建面向舱室布局优化的多维度评价体系,系统梳理相关优化算法,分析当前技术瓶颈,并提出未来研究方向,为船舶舱室智能化设计提供理论与技术支撑。首先,总结提出一套面向船舶舱室空间布局优化的多维度评价体系,该体系综合考虑了功能关联性、人类活动和环境等多方面因素,为后续优化算法的选择与设计提供了清晰的目标和方向。然后,系统回顾近年来研究人员在船舶舱室布局优化领域提出的重要算法,包括并不限于遗传算法、引力搜索算法、整数规划方法以及群组运动仿真驱动方法等,并总结梳理上述优化算法用于求解高质量空间布局的研究成果。接着,构建优化方法与评价指标之间的支撑关系表,并对主流方法进行多维度对比分析,并同时针对多层甲板复杂场景,对比单、多层差异、总结实例并分析不足。研究发现,尽管各类算法在船舶舱室空间布局优化领域取得显著进展,但仍存在诸多局限性,如普遍未从微观执行层面考虑问题、难以对多层甲板布局进行高效建模等。最后,从构建专业领域数据集、创新智能优化算法以及设计人在回路深度强化学习框架等多个角度对未来的研究方向提出展望。

     

    Abstract: 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.

     

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