A pre-tendering project prioritization decision support system for contractors based on artificial neural network and AHP Fuzzy-TOPSIS

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.