A multi-attribute model for construction site layout using intuitionistic fuzzy logic

被引:33
作者
Ning, Xin [1 ,2 ]
Ding, L. Y. [1 ]
Luo, H. B. [1 ]
Qi, S. J. [3 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Civil Engn & Mech, Wuhan, Hubei Province, Peoples R China
[2] Dongbei Univ Finance & Econ, Sch Investment & Construct Management, Dalian, Liaoning Provin, Peoples R China
[3] Huaqiao Univ, Coll Civil Engn, Xiamen, Fujian Province, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Construction site layout planning; Intuitionistic fuzzy logic; TOPSIS; Multi-attribute decision making; ANALYTIC HIERARCHY PROCESS; GENETIC ALGORITHMS; DECISION-MAKING; PROJECTS;
D O I
10.1016/j.autcon.2016.09.008
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Most researchers have concentrated on studying optimization models to produce optimal construction site layout plans using different algorithms, while the overall method for evaluating and selecting the best site layout generated from optimization models has received less attention. In an optimization model, construction cost is generally considered in the objective function. However, several objectives, such as security and tie-in with external transportation, are difficult to quantify in the objective function and were not considered in previous studies. This paper focuses on evaluating and selecting the construction site layout considering qualitative objectives. An intuitionistic fuzzy multi-attribute decision-making model is developed that combines intuitionistic fuzzy set theory and the technique for order preference by similarity to the ideal solution (TOPSIS). This model overcomes the shortcomings of a traditional fuzzy set when describing ambiguous and unclear circumstances by using membership functions. The application of this model for site layout selection is shown to be reasonable and effective based on data from a real construction project. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:380 / 387
页数:8
相关论文
共 32 条
[1]   Dynamic site layout planning through minimization of total potential energy [J].
Andayesh, Mohsen ;
Sadeghpour, Farnaz .
AUTOMATION IN CONSTRUCTION, 2013, 31 :92-102
[2]   INTUITIONISTIC FUZZY-SETS [J].
ATANASSOV, KT .
FUZZY SETS AND SYSTEMS, 1986, 20 (01) :87-96
[3]   A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method [J].
Boran, Fatih Emre ;
Genc, Serkan ;
Kurt, Mustafa ;
Akay, Diyar .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (08) :11363-11368
[4]   LAYOUT DESIGN USING THE ANALYTIC HIERARCHY PROCESS [J].
CAMBRON, KE ;
EVANS, GW .
COMPUTERS & INDUSTRIAL ENGINEERING, 1991, 20 (02) :211-229
[5]   Site pre-cast yard layout arrangement through genetic algorithms [J].
Cheung, SO ;
Tong, TKL ;
Tam, CM .
AUTOMATION IN CONSTRUCTION, 2002, 11 (01) :35-46
[6]  
Dulaimi M.F., 2002, CONSTR MANAG ECON, V20, P601, DOI DOI 10.1080/01446190210159890
[7]   New mathematical optimization model for construction site layout [J].
Easa, Said M. ;
Hossain, K. M. A. .
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT-ASCE, 2008, 134 (08) :653-662
[8]   A hybrid AI-based system for site layout planning in construction [J].
Elbeltagi, E ;
Hegazy, T .
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2001, 16 (02) :79-93
[9]  
Elbeltagi E., 2001, Construction Management and Economics, V19, P689, DOI DOI 10.1080/01446190110066713
[10]   Integrating the analytic hierarchy process and graph theory to model facilities layout [J].
Foulds, LR ;
Partovi, FY .
ANNALS OF OPERATIONS RESEARCH, 1998, 82 (0) :435-451