舰船管路布置PG-MACO优化方法

doi:10.16183/j.cnki.jsjtu.2022.508

上海交通大学学报 ›› 2024, Vol. 58 ›› Issue (7): 1027-1035.doi: 10.16183/j.cnki.jsjtu.2022.508

舰船管路布置PG-MACO优化方法

林焰, 金庭宇(), 杨宇超

大连理工大学 a. 船舶工程学院;b. 工业装备结构分析国家重点实验室,辽宁大连 116024

收稿日期:2022-12-09 修回日期:2023-02-26 接受日期:2023-04-06 出版日期:2024-07-28 发布日期:2024-07-26
通讯作者: 金庭宇,硕士生;E-mail:22003161@mail.dlut.edu.cn.
作者简介:林焰(1963-),教授,博士生导师,从事船舶与海洋结构物数字化设计方法与软件开发研究.
基金资助:
国家重点实验室专项基金(S18315);中核绿色建造技术与装备重点实验室开放基金项目(CNNC-STGCL-KFKT-2022-001)

PG-MACO Optimization Method for Ship Pipeline Layout

LIN Yan, JIN Tingyu(), YANG Yuchao

School of Naval Architecture and Ocean Engineering; b. State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, Liaoning, China

Received:2022-12-09 Revised:2023-02-26 Accepted:2023-04-06 Online:2024-07-28 Published:2024-07-26

摘要/Abstract

摘要：

针对舰船管路设计效率低下的问题提出一种管路布置优化方法.综合考虑安全性、经济性、协调性和可操作性等工程背景建立优化数学模型,改进蚁群算法在处理混合管路布置工况下的缺陷,提出优化可行解搜索的空间状态转移策略,提升信息素启发效果并加速算法收敛的信息素扩散机制,面向混合管路布置工况设计多蚁群协同进化机制.基于二次开发技术实现本方法在第三方设计软件上的应用,采用核级一回路管道布置工程案例进行验证.结果表明信息素高斯扩散多蚁群优化(PG-MACO)算法的性能和布置效果优于传统蚁群算法,寻路效率提升58.38%,收敛代数缩短43.24%,布置结果中管路长度缩短33.88%,管路折弯次数减少41.67%,验证了本方法的有效性和工程实用性.

关键词: 舰船管路, 布局优化, 蚁群优化算法, 信息素扩散

Abstract:

Aimed at the problem of low efficiency of ship pipeline design, an optimization method of pipeline layout is proposed. An optimization mathematical model is established by comprehensively considering the engineering background of safety, economy, coordination and operability, and the defects of ant colony optimization algorithm in dealing with mixed pipeline layout conditions are improved. A spatial state transition strategy for optimizing feasible solution search, a pheromone diffusion mechanism for improving pheromone inspiration effect and accelerating algorithm convergence are proposed, and a multi-ant colony co-evolution mechanism is designed for mixed pipeline layout conditions. Based on the secondary development technology, the application of this method in the third-party design software is realized, and verified by a nuclear primary pipeline layout project. The results show that the pheromone Gaussian diffusion multi ant colony optimization (PG-MACO) algorithm has a better performance and layout effect than the traditional ant colony algorithm. The routing efficiency is improved by 58.38%, the convergence algebra is shortened by 43.24%, the pipeline length is shortened by 33.88%, and the number of pipeline bends is reduced by 41.67%, which verifies the effectiveness and engineering practicability of the proposed method.

Key words: ship pipeline, layout optimization, ant colony optimization algorithm, pheromone diffusion

中图分类号:

林焰, 金庭宇, 杨宇超. 舰船管路布置PG-MACO优化方法[J]. 上海交通大学学报, 2024, 58(7): 1027-1035.

LIN Yan, JIN Tingyu, YANG Yuchao. PG-MACO Optimization Method for Ship Pipeline Layout[J]. Journal of Shanghai Jiao Tong University, 2024, 58(7): 1027-1035.

图/表 13

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管路序号	起点接口/mm	终点接口/mm
P1	(6 500, 4 975, 1 700)	(7 220, 5 100, 1 000)
P2	(6 500, 7 170, 1 700)	(7 220, 7 100, 1 000)
P3	(1 000, 520, 4 750)	(3 700, 460, 3 700)
P4	(1 000, 1 700, 5 500)	(930, 1 400, 7 100)
P5	(930, 1 500, 7 400)	(75, 3 240, 4 140)
P6	(1 000, 2 300, 3 200)	(75, 3 240, 3 800)
P7-1	(6 150, 4 975, 2 125)	(930, 1 400, 7 500)
P7-2	(6 150, 4 975, 2 125)	(6 150, 7 170, 2 125)
P8-1	(8 980, 5 720, 3 520)	(7 780, 5 100, 1 000)
P8-2	(8 980, 5 720, 3 520)	(7 780, 7 100, 1 000)

设备序号	极小对角点/mm	极大对角点/mm
Equ_1	(0, 3 162, 3 831)	(150, 3 377, 4 111)
Equ_2	(857, 1 312, 7 138)	(1 007, 1 497, 7 483)
Equ_3	(174, 516, 3 051)	(1 825, 2 273, 5 483)
Equ_4_1	(3 729, 157, 3 241)	(5 270, 758, 4 052)
Equ_4_2	(8 682, 5 751, 3 064)	(9 283, 7 293, 3 875)
Equ_5_1	(6 169, 4 824, 1 725)	(6 650, 5 124, 2 725)
Equ_5_2	(6 169, 7 024, 1 725)	(6 650, 7 324, 2 725)
Equ_6_1	(7 249, 4 999, 874)	(7 750, 5 200, 1 125)
Equ_6_2	(7 249, 6 999, 874)	(7 750, 7 200, 1 125)

参数	取值
种群数量	20
迭代次数	100
信息素总量	500
信息素挥发因子	0.4
信息素启发因子	2
距离启发因子	2
高斯分布期望	0
高斯分布方差基值	3
高斯分布方差下限	1

参数	布置方案比较		降幅/%
参数	传统蚁群	PG-MACO	降幅/%
个体寻路时间/ms	1 110.18	462.05	58.38
收敛代数	37	21	43.24
管路长度/mm	51 650	34 150	33.88
折弯数	36	21	41.67

管路序号	GA-A^*		PG-MACO
管路序号	长度/mm	折弯次数	长度/mm	折弯次数
P1	5 700	3	5 500	4
P2	1 850	3	1 800	3
P3	2 900	3	2 650	3
P4	1 400	3	1 250	3
P5	4 000	3	3 950	3
P6	18 450	6	13 400	7
P7	15 400	7	15 450	9
P8	8 300	4	8 100	4
总计	58 000	32	52 100	36

舰船管路布置PG-MACO优化方法

PG-MACO Optimization Method for Ship Pipeline Layout

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