[1]卢梅,杨佳兴,张喜临.基于BP神经网络及熵权灰靶法的分包商选择研究[J].西安建筑科技大学学报(自然科学版),2019,51(03):447-456.[doi:10.15986/j.1006-7930.2019.03.021]
　LU Mei,YANG Jiaxing,ZHANG Xilin.Research on subcontractor selection based on BP neural network and entropy grey target method[J].J. Xi’an Univ. of Arch. & Tech.(Natural Science Edition),2019,51(03):447-456.[doi:10.15986/j.1006-7930.2019.03.021]
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基于BP神经网络及熵权灰靶法的分包商选择研究()
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西安建筑科技大学学报（自然科学版）[ISSN:1006-7930/CN:61-1295/TU]

卷:
51
期数:
2019年03期
页码:
447-456
栏目:
出版日期:
2019-06-30

文章信息/Info

Title:
Research on subcontractor selection based on BP neural network and entropy grey target method
文章编号:
1006-7930(2019)03-0447-10
作者:
卢梅1; 杨佳兴1 ; 张喜临2
（1. 西安建筑科技大学 管理学院，陕西 西安 710055；2. 陕西建工第三建设集团有限公司，陕西 西安710054）
Author(s):
LU Mei1;  YANG Jiaxing1;  ZHANG Xilin2
（1.School of management, Xi′an Univ. of Arch. & Tech.，Xi′an 710055, China；2. SCEGC No.3 Construction Engineering Group Company Ltd, Xi′an 710054, China）
关键词:
分包商选择; BP神经网络; 熵权法; 灰靶决策
Keywords:
subcontractor selection;  BP neural network;  entropy weight method;  grey target decision
分类号:
TU74
DOI:
10.15986/j.1006-7930.2019.03.021
文献标志码:
A
摘要:
在建筑工程分包专业化发展的趋势下，项目分包商的选择变得尤为重要，分包商选择不当会给施工带来更大的风险.同时分包商招标时也存在着控制价难以确定、评价方法单一等问题.为此提出了基于BP神经网络和熵权灰靶法的两阶段分包商选择模型.首先提出了转换值概念，找到了承包价与分包价之间的转换关系，以S建筑公司的以往工程数据为基础运用BP神经网络预测分包招标控制价.然后建立综合指标评价体系，利用熵权法确定指标权重，再用灰靶决策确定最优分包商.最后以S建筑公司的实际的分包过程为例，验证了该选择模型的可行性.为分包商的选择提供了新思路.
Abstract:
With the development of subcontractor specialization, the choice of subcontractor becomes more and more important. The improper choice of subcontractor will bring more risks to construction. At the same time, subcontractors also have problems such as difficulty in determining control price and single evaluation method when bidding. Therefore, a two stage subcontractor selection model based on BP neural network and entropy weight grey target method is proposed. Firstly, the conversion value algorithm is proposed, and the conversion relationship between the contract price and the subcontract price is found. Based on the previous engineering data of S Construction Company, BP neural network is used to predict the subcontract tender control price. Then the comprehensive index evaluation system is established, the index weight is determined by entropy weight method, and the optimal subcontractor is determined by grey target decision. Finally, taking the actual subcontracting process of S Construction Company as an example, the feasibility of the selection model is verified. It provides new ideas for subcontractors’ choice.

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备注/Memo

备注/Memo:
收稿日期:2018-10-07修改稿日期:2019-05-11
基金项目:陕西省重点科技创新团队计划基金项目（2017KCT-14）
第一作者:卢梅（1971-），副教授，研究方向为项目管理、建筑经济.E-mail:1822831317@qq.com
通信作者:杨佳兴（1993-），硕士研究生，研究方向为工程经济与管理.E-mail:1170160569@qq.com
更新日期/Last Update: 2019-07-22