[1]陈 超,陈振中.基于遗传算法的综合布线路径布局研究[J].南京师范大学学报(工程技术版),2020,(04):051-56.[doi:10.3969/j.issn.1672-1292.2020.04.008]
 Chen Chao,Chen Zhenzhong.Research on Route Planning of Generic CablingBased on Genetic Algorithm[J].Journal of Nanjing Normal University(Engineering and Technology),2020,(04):051-56.[doi:10.3969/j.issn.1672-1292.2020.04.008]
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基于遗传算法的综合布线路径布局研究
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年04期
页码:
051-56
栏目:
计算机科学与技术
出版日期:
2020-12-15

文章信息/Info

Title:
Research on Route Planning of Generic CablingBased on Genetic Algorithm
文章编号:
1672-1292(2020)04-0051-06
作者:
陈 超1陈振中2
(1.江苏卓易信息科技股份有限公司,江苏 宜兴 214200)(2.东华大学机械工程学院,上海 201620)
Author(s):
Chen Chao1Chen Zhenzhong2
(1.Jiangsu Eazytec Co.,Ltd.,Yixing 214200,China)(2.College of Mechanical Engineering,Donghua University,Shanghai 201620,China)
关键词:
遗传算法综合布线建筑智能化路径规划
Keywords:
genetic algorithmgeneric cablingbuilding intelligencepath planning
分类号:
TM715
DOI:
10.3969/j.issn.1672-1292.2020.04.008
文献标志码:
A
摘要:
以综合布线系统的路径规划为研究对象,对布线路径中的公共路径和最短路径的双目标进行统筹规划,以满足不同情况下的不同施工需求. 首先给出了综合布线决策的整数规划模型,采用遗传算法构建了一种新的综合布线优化算法,用于进行综合布线路径规划的设计与研究. 在遗传算法的基础上,通过加权组合的方式实现公共路径和最短路径的协调,其中公共路径越长越节约工期,最短路径越长越节约成本. 最后,通过仿真对所提模型和方法的有效性进行了验证.
Abstract:
In this paper,the path planning of generic cabling system is taken as the research object,and the dual objectives of the public path and the shortest path are planned as a whole to meet the different construction needs in different situations. For this reason,this paper first gives the integer programming model of PDS decision,and uses genetic algorithm to build a new PDS optimization algorithm for the design and research of PDS path planning. Based on genetic algorithm,we realize the coordination of public path and shortest path by weighted combination,in which the longer the public path is,the shorter the construction period is,and the longer the shortest path is,the more cost is saved. Finally,through the simulation,the validity of the proposed model and method is verified.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-04-22.
基金项目:上海市自然科学基金面上项目(19ZR1401600).
通讯作者:陈振中,博士,副研究员,研究方向:工程优化. E-mail:zhenzh.chen@dhu.edu.cn
更新日期/Last Update: 2020-12-15