Review of research on ship compartment spatial layout optimization

In ship design, the spatial layout of compartments is crucial not only for enhancing navigational safety and operational efficiency but also for ensuring crew comfort and overall ship performance. This paper aims to establish 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 ship compartment design. First, a multi-dimensional evaluation system for optimizing ship compartment spatial layout is summarized and proposed. This system comprehensively accounts for factors such as functional correlation, absolute position, human activities, environmental conditions, and weight distribution, offering clear objectives and guidance for the selection and implementation of subsequent optimization algorithms. Taking into account the differences in functional requirements and design priorities among various ship types, as well as the availability of practical data, users can flexibly select applicable indicator combinations from this evaluation system to conduct targeted scientific assessments for specific scenarios. Next, a systematic review is presented of the major algorithms developed in recent years for ship compartment layout optimization. These include, but are 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 producing high-quality spatial layouts are systematically summarized and organized. A support relationship table between optimization methods and evaluation indicators is then constructed. The mainstream optimization methods are reviewed and compared across multiple dimensions, including algorithm principles, solution efficiency, multi-objective processing capability, and engineering applicability, to assess their suitability for ship compartment layout optimization tasks. For complex multi-deck scenarios, the study compares the differences between single-deck and multi-deck spatial layout optimization, summarizes examples of multi-deck spatial layout optimization, and identifies existing limitations. Furthermore, the rationality and scientific validity of the proposed evaluation system are verified through case studies of multi-deck configurations. The findings indicate that although significant progress has been made in ship compartment spatial layout optimization, several challenges remain, such as limited consideration of micro-execution-level issues and difficulties in efficiently modeling multi-deck layouts. Finally, this paper outlines future research directions from multiple perspectives, including the development of high-quality ship compartment layout datasets, the exploration of novel intelligent optimization algorithms, and the integration of human-in-the-loop deep reinforcement learning frameworks.