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Please use this identifier to cite or link to this item: http://hdl.handle.net/2031/6547

Title: A pre-tendering project prioritization decision support system for contractors based on artificial neural network and AHP Fuzzy-TOPSIS
Other Titles: Jian li cheng jian shang tou biao qian qi gong cheng pai xu jue ce zhi chi de ren gong shen jing wang luo mo hu xi tong
建立承建商投標前期工程排序決策支持的人工神經網絡模糊系統
Authors: Guo, Lili ( 郭麗麗)
Department: Department of Civil and Architectural Engineering
Degree: Master of Philosophy
Issue Date: 2011
Publisher: City University of Hong Kong
Subjects: Project management -- Decision making.
Construction industry -- Management.
Decision support systems -- Mathematical models.
Neural networks (Computer science)
Notes: CityU Call Number: HD69.P75 G88 2011
xiii, 167 leaves : ill. 30 cm.
Thesis (M.Phil.)--City University of Hong Kong, 2011.
Includes bibliographical references (leaves 144-152)
Type: thesis
Abstract: In the developing countries, such as mainland China and India, the economic conditions are flourishing. It is very common for contractors to face several alternative projects at the same time. Then the decision makers (DMs) of the contractor have to decide the pre-tendering project prioritization of the potential projects for bidding; thus the pre-tendering project prioritization (PTPP) problem is proposed. In order to handle the PTPP problem, this research proposes the PTPP decision support system (DSS). The researcher firstly reviewed the pre-tendering theories and collected 120 influencing factors of the PTPP problem from previous researchers. Then these 120 factors are screened to 69 factors and categorized into 5 groups. Then these 69 factors are further reduced to 24 key factors. Finally the researcher conducted an industry survey to obtain seven key factors as the decision criteria. After that, the researcher presented the proposed PTPP decision support system, where two modules are integrated. Module one is an Artificial Neural Network (ANN) model to make use of past projects‘ data which is stored in the Management Information System of the company. Module two adopted the Analytic Hierarchy Process (AHP) Fuzzy-Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method to handle the current situation of the company. Then the proposed PTPP decision support system was verified by a case study in Shanghai, China. The result of the proposed PTPP DSS is efficient in this case. Finally, the advantages and limitations of the proposed PTPP decision support system as well as the future research works are concluded.
Online Catalog Link: http://lib.cityu.edu.hk/record=b4086341
Appears in Collections:CA - Master of Philosophy

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