基于自适应粒子群算法的船舶机舱双层布局优化研究
A two-layer layout optimization method for Marine engine room based on adaptive particle swarm optimization
杨帆 1张佳宁 1刁峰 2苏勇瑞1
作者信息
- 1. 大连海事大学船舶与海洋工程学院,辽宁大连 116033
- 2. 中国船舶科学研究中心,江苏无锡 214000
- 折叠
摘要
为提高船舶机舱的智能设计水平,提出一种针对于船舶机舱设备布局的智能优化方法.以某船机舱为例,通过分析船舶机舱设备对于机舱内部温度的耐受性、通风需求、以及设备自重对于船舶重心位置的影响,建立船舶机舱设备的分层评分机制,实现设备在机舱内部的分层布置.从设备系统群关系、流通成本、倾斜力矩、吊装需求等6个角度出发对机舱双层布局进行分析并建立数学模型,运用罚函数法处理约束条件,运用自适应粒子群算法求解该数学模型,得出布局方案并进行合理性分析.使用该方法优化之后,同一系统或邻接性较强的设备紧密布置,非邻接性设备分散布置,设备之间的流通成本降低约12％,吊装距离减少约100％,倾斜力矩之和降低约130％.结果分析表明,该方法能有效地解决船舶机舱的布局优化问题,可为解决类似的布局优化问题提供参考.
Abstract
To enhance the intelligence level of ship engine room design,a smart optimization method is proposed for the layout of ship engine room equipment.For example,taking a certain ship's engine room as an example,a hierarchical scoring mechanism for ship's engine room equipment is established by analyzing the equipment's tolerance to internal tem-perature,ventilation requirements,and the impact of equipment self-weight on the ship's center of gravity position.This mechanism allows for a layered arrangement of equipment within the engine room.From six perspectives including equip-ment system grouping relationships,circulation costs,tilting moments,and lifting requirements,an analysis of the double-layer layout of the engine room is conducted,and a mathematical model is established.The penalty function method is used to handle the constraints,and the adaptive particle swarm algorithm is used to solve the mathematical model.The layout plan is obtained and its rationality is analyzed.After optimizing this method,devices within the same system or with strong adja-cency are arranged closely,while devices without adjacency are dispersed.The circulation cost between devices is reduced by approximately 12％,the lifting distance is reduced by approximately 100％,and the sum of tilting torques is reduced by approximately 130％.The analysis of the results shows that this method can effectively solve the layout optimization prob-lem of ship cabins and can provide references for solving similar layout optimization problems.
关键词
机舱布局/评分机制/数学模型/自适应粒子群算法Key words
cabin layout/scoring mechanism/mathematical model/adaptive particle swarm algorithm引用本文复制引用
基金项目
工业与信息化部智能技术试验船关键技术研究项目(CJ01N20)
出版年
2024
NETL
NSTL
万方数据