基于需求量预测和GIS的装配式PC构件厂选址优化方法

周光权; 程婷; 刘勇; 何正亚; 蔡梦雅

doi:10.19713/j.cnki.43-1423/u.T20230717

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基于需求量预测和GIS的装配式PC构件厂选址优化方法

工程经济•工程管理•规划设计 | 更新时间：2023-12-05

- 基于需求量预测和GIS的装配式PC构件厂选址优化方法
- Optimal site selection method for prefabricated PC components plants based on demand forecasting and GIS
- 铁道科学与工程学报 2023年20卷第11期页码：4389-4399
- 作者机构：
  
  1.安徽省建筑科学研究设计院绿色建筑与装配式建造安徽省重点实验室，安徽合肥230031
  2.南昌航空大学土木建筑学院，江西南昌 330063
  3.河海大学商学院，江苏南京 211100
  4.北京市公联公路联络线有限责任公司，北京 100161
- 作者简介：
  
  程婷(1996—)，女，河南新乡人，博士研究生，从事项目管理、河湖管理等研究；E-mail：chengting@hhu.edu.cn
- 基金信息：
  
  绿色建筑与装配式建造安徽省重点实验室资助项目(2022-JKYL-003);南昌航空大学博士启动基金资助项目(EA202211137)
- DOI：10.19713/j.cnki.43-1423/u.T20230717
  中图分类号：
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周光权,程婷,刘勇等.基于需求量预测和GIS的装配式PC构件厂选址优化方法[J].铁道科学与工程学报,2023,20(11):4389-4399.

ZHOU Guangquan,CHENG Ting,LIU Yong,et al.Optimal site selection method for prefabricated PC components plants based on demand forecasting and GIS[J].Journal of Railway Science and Engineering,2023,20(11):4389-4399.
周光权,程婷,刘勇等.基于需求量预测和GIS的装配式PC构件厂选址优化方法[J].铁道科学与工程学报,2023,20(11):4389-4399. DOI： 10.19713/j.cnki.43-1423/u.T20230717.

ZHOU Guangquan,CHENG Ting,LIU Yong,et al.Optimal site selection method for prefabricated PC components plants based on demand forecasting and GIS[J].Journal of Railway Science and Engineering,2023,20(11):4389-4399. DOI： 10.19713/j.cnki.43-1423/u.T20230717.

摘要

装配式建筑作为建筑工业化和信息化深度融合的产物，近年来发展势头迅猛。为满足日益增长的装配式混凝土(PC)构件的市场需求，需要科学布局PC构件厂使其形成规模化效应，为此提出一种PC构件厂的选址优化方法。首先，基于市场供求理论，通过灰色预测模型和二次指数平滑法构建PC构件需求量综合预测模型，以江西省为例，对未来6 a构件需求量进行预测，避免造成PC构件产能过剩，预测结果显示江西省未来3 a内对PC构件的需求量将会急剧上升，亟需增设新的PC构件厂。其次，调研现阶段PC构件厂布局等情况，并利用Python获取城市建设用地、交通网络、水网、学校、医院、旅游景点、政府机关、高密度居民区等地理信息数据，在PC构件厂选址原则的约束下，通过地理信息系统(GIS)平台对所获取的空间信息数据等进行叠置分析和擦除分析，得到初步选址点。最后，建立最优运输成本模型，基于模型假设和约束条件进行求解，确定PC构件厂的选址位置。结果表明：采用选址优化模型，能够将624个初步选址点优化为80个最佳选址点，验证了选址优化模型的有效性，形成了PC构件厂的优化布局方案。研究结果可为PC构件厂选址提供一定的参考，有助于装配式建筑产业的进一步发展。

Abstract

As a product of deep integration of construction industrialization and information, prefabricated building has been developing rapidly over recent years. In order to meet the growing market demand for prefabricated concrete (PC) components, it is necessary to scientifically plan the layout of PC component factories to achieve economies of scale. To this end, a location optimization method for PC component factories was proposed. Based primarily on the theory of market supply and demand, the grey prediction model and double exponential smoothing method were used to construct a comprehensive prediction model for the demand of PC components, which can predict the demand of PC components in Jiangxi Province over the next six years to avoid PC component manufacturers’ overcapacity. The results indicate that the demand for PC components in Jiangxi Province will rise inexorably within the next six years and new PC component factories are urgently needed. Furthermore, the current layout of PC component factories is investigated. The Python technology is used to obtain geographic information data, such as urban construction land, transportation networks, water networks, schools, hospitals, tourist attractions, government agencies, and high-density residential areas, etc. Under the constraints of the site selection principles for PC component factories, the Geographic Information System (GIS) platform is used for performing overlay analysis and erase analysis on the acquired spatial information data obtaining preliminary site selection points. The optimal transportation cost model is established, and determine the site selection location of the final PC component factories. The results indicate that the optimization model can optimize 624 preliminary site points into 80 best site selection points, verifying the effectiveness of the location optimization model in forming an optimized layout plan for PC component factories. The research results could provide a certain reference for the site selection of PC factories, and contribute to the further development of the prefabricated construction industry.

关键词

装配式建筑灰色系统理论综合预测模型GIS优化选址

Keywords

prefabricated buildingsgrey system theorycomprehensive prediction modelGISsite selection optimization

references

中华人民共和国中央人民政府. 国务院办公厅关于大力发展装配式建筑的指导意见[EB/OL]. (2016-09-30)[2023-05-08]. https://www.gov.cn/zhengce/content/2016-09/30/content_5114118.htmhttps://www.gov.cn/zhengce/content/2016-09/30/content_5114118.htm.

The Central People’s Government of the People’s Republic of China. Guiding opinions of the general office of the state council on vigorously developing prefabricated buildings[EB/OL]. (2016-09-30)[2023-05-08]. https://www.gov.cn/zhengce/content/2016-09/30/content_5114118.htmhttps://www.gov.cn/zhengce/content/2016-09/30/content_5114118.htm.

苟寒梅, 毛超, 董茜月. 预制装配式与现浇式建筑施工成本对比研究[J]. 建筑经济, 2018, 39(3): 71-74.

GOU Hanmei, MAO Chao, DONG Qianyue. Comparative analysis of the construction cost of prefabricated assembly construction and cast-in-place concrete structure[J]. Construction Economy, 2018, 39(3): 71-74.

AZMAN M N A, AHMAD M S S, HAMID Z A, et al. The selection of IBS precast manufacturing plant in Malaysia using GIS[J]. Malaysian Construction Research Journal, 2012, 10(1): 77-90.

NUHU S K, MANAN Z A, WAN ALWI S R, et al. Roles of geospatial technology in eco-industrial park site selection: state-of-the-art review[J]. Journal of Cleaner Production, 2021, 309: 127361.

WANG Shuqiang, RUAN Yuke, HU Wanwei. Site selection of precast concrete component factory based on PCA and GIS[J]. Advances in Civil Engineering, 2022, 2022: 1-12.

罗倩蓉, 董茜月, 曾德珩. 基于模糊层次分析法的装配式建筑PC构件厂选址[J]. 土木工程与管理学报, 2018, 35(3): 111-117.

LUO Qianrong, DONG Xiyue, ZENG Deheng. Location selection of PC factory based on analytic hierarchy process[J]. Journal of Civil Engineering and Management, 2018, 35(3): 111-117.

王淑嫱, 胡婉薇, 卢仲兴. 基于AHP与GIS技术的PC构件厂选址: 以武汉市汉南区为例[J]. 土木工程与管理学报, 2020, 37(2): 115-121.

WANG Shuqiang, HU Wanwei, LU Zhongxing. Site selection of PC factory based on AHP and GIS technology: taking Hannan district of Wuhan as an example[J]. Journal of Civil Engineering and Management, 2020, 37(2): 115-121.

仇国芳, 赵阳艳. 绿色装配式建筑产业园区选址决策研究[J]. 建筑节能, 2018, 46(9): 131-136.

QIU Guofang, ZHAO Yangyan. Location decision of green assembled construction industry park[J]. Building Energy Efficiency, 2018, 46(9): 131-136.

周光权, 程婷, 陈思婷. 基于免疫优化算法的装配式建筑构件生产基地选址研究[J]. 铁道科学与工程学报, 2020, 17(9): 2430-2436.

ZHOU Guangquan, CHENG Ting, CHEN Siting. Research on location selection of assembly building component production base based on immune optimization algorithm[J]. Journal of Railway Science and Engineering, 2020, 17(9): 2430-2436.

李雨萱, 龚哲宇, 符瑛, 等. 基于景观理论的长沙铁路物流园区布局规划研究[J]. 铁道科学与工程学报, 2022, 19(5): 1222-1233.

LI Yuxuan, GONG Zheyu, FU Ying, et al. Layout planning of Changsha Railway Logistics Park based on landscape theory[J]. Journal of Railway Science and Engineering, 2022, 19(5): 1222-1233.

李琴琴. 最优定权组合预测模型在区域物流量预测中的应用[J]. 物流科技, 2016, 39(6): 34-38.

LI Qinqin. The application of the optimal weighting combination model in regional logistics volume forecasting[J]. Logistics Sci-Tech, 2016, 39(6): 34-38.

赵晓艳, 刘天娇, 周波, 等. 灰色模型GM(1,1)的平滑改进及其应用[J]. 东北电力大学学报, 2006, 26(4): 63-66.

ZHAO Xiaoyan, LIU Tianjiao, ZHOU Bo, et al. The smoothing improvement and the application of grey model GM(1,1)[J]. Journal of Northeast Dianli University, 2006, 26(4): 63-66.

INNELLA F, ARASHPOUR M, BAI Yu. Lean methodologies and techniques for modular construction: chronological and critical review[J]. Journal of Construction Engineering and Management, 2019, 145(12): 04019076.

SANDBERG E, BILDSTEN L. Coordination and waste in industrialised housing[J]. Construction Innovation, 2011, 11(1): 77-91.

XU Jiuping, SONG Xiaoling, WU Yimin, et al. GIS-modelling based coal-fired power plant site identification and selection[J]. Applied Energy, 2015, 159: 520-539.

肖绪文, 曹志伟, 刘星, 等. 我国建筑装配化发展的现状、问题与对策[J]. 建筑结构, 2019, 49(19): 1-4.

XIAO Xuwen, CAO Zhiwei, LIU Xing, et al. Status, problems and countermeasures of prefabricated buildings in China[J]. Building Structure, 2019, 49(19): 1-4.

中华人民共和国住房和城乡建设部. 装配式混凝土建筑技术标准: GB/T 51231—2016[S]. 北京: 中国建筑工业出版社, 2017.

Ministry of Housing and Urban-Rural Development of the People’s Republic of China. Technical standard for assembled buildings with concrete structure: GB/T 51231—2016[S]. Beijing: China Architecture & Building Press, 2017.

龚建锋, 马健. PC构件生产基地的选址与投资分析方法[J]. 浙江建筑, 2019, 36(4): 54-59.

GONG Jianfeng, MA Jian. Site selection and investment analysis method of PC component production base[J]. Zhejiang Construction, 2019, 36(4): 54-59.

江西省人民政府. 江西省人民政府办公厅关于促进建筑业转型升级高质量发展的意见[EB/OL]. (2020-11-11)[2023-05-08]. https://www.jiangxi.gov.cn/art/2020/11/16/art_4975_2893861.htmlhttps://www.jiangxi.gov.cn/art/2020/11/16/art_4975_2893861.html.

The People’s Government of Jiangxi Province. Opinions of the general office of the people’s government of Jiangxi provincial on promoting the transformation, upgrading and high-quality development of construction industry[EB/OL]. (2020-11-11)[2023-05-08]. https://www.jiangxi.gov.cn/art/2020/11/16/art_4975_2893861.htmlhttps://www.jiangxi.gov.cn/art/2020/11/16/art_4975_2893861.html.

侯丽敏, 马国峰. 基于灰色线性回归组合模型铁路客运量预测[J]. 计算机仿真, 2011, 28(7): 1-3.

HOU Limin, MA Guofeng. Forecast of railway passenger traffic based on a grey linear regression combined model[J]. Computer Simulation, 2011, 28(7): 1-3.

徐翔燕, 侯瑞环. 基于GM(1,1)-SVM组合模型的中长期人口预测研究[J]. 计算机科学, 2020, 47(S1): 485-487.

XU Xiangyan, HOU Ruihuan. Medium and long-term population prediction based on GM(1,1)-SVM combination model[J]. Computer Science, 2020, 47(S1): 485-487.

黄学林, 王观虎, 龙小勇, 等. 机场道面预防性养护评价指标综合改进灰色预测模型[J]. 铁道科学与工程学报, 2021, 18(12): 3228-3238.

HUANG Xuelin, WANG Guanhu, LONG Xiaoyong, et al. Comprehensive improvement of grey prediction model of airport pavement preventive maintenance evaluation index[J]. Journal of Railway Science and Engineering, 2021, 18(12): 3228-3238.

BATES J M, GRANGER C W J. The combination of forecasts[J]. Journal of the Operational Research Society, 1969, 20(4): 451-468.

贡文伟, 黄晶. 基于灰色理论与指数平滑法的需求预测综合模型[J]. 统计与决策, 2017(1): 72-76.

GONG Wenwei, HUANG Jing. A demand forecast model based on the gray theory and exponential smoothing method[J]. Statistics & Decision, 2017(1): 72-76.

邓聚龙. 灰预测与灰决策[M]. 修订版. 武汉: 华中科技大学出版社, 2002: 111-134.

DENG Julong. Grey prediction and grey decision-making[M]. Revised ed. Wuhan: Huazhong University of Science and Technology Press, 2002: 111-134.

李新春, 何世兵, 张超. 装配式建筑预制构件运输费浅析[J]. 重庆建筑, 2019, 18(10): 61-63.

LI Xinchun, HE Shibing, ZHANG Chao. Transportation cost of prefabricated components in prefabricated buildings[J]. Chongqing Architecture, 2019, 18(10): 61-63.

张超. 地理信息系统实习教程[M]. 北京: 高等教育出版社, 2000.

ZHANG Chao. Practice course of geographic information system[M]. Beijing: Higher Education Press, 2000.

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