TY - GEN
T1 - Modeling Bid/No bid decision using adaptive neuro fuzzy inference system (ANFIS)
T2 - 2014 Construction Research Congress: Construction in a Global Network, CRC 2014
AU - Polat, Gul
AU - Bingol, Befrin Neval
AU - Uysalol, Enis
PY - 2014
Y1 - 2014
N2 - Bid/no bid decisions are crucial for the business continuity of a contractor. Thus, the decision should be made carefully within the context of the short- and long-term strategy of the organization. Despite the availability of several models, this decision commonly is made based on past experience and subjective judgments. This study aims to show how ANFIS can be used as a decision support tool by contractors during the bid/no bid decision process for international construction projects. Review of the literature revealed that 52 factors may affect a contractor's bid/no bid decision. These factors were categorized into six main groups, which are bidding documents-related factors, contractor-related factors, project-related factors, contract-related factors, host country-related factors, and opportunity-related factors. Having identified these factors, a questionnaire was designed to identify each factor's relative importance. The questionnaire was applied to a large-scale contractor, and actual data from 151 international projects were obtained. An ANFIS model was developed via MATLAB software program using the collected data. The proposed ANFIS model integrates the learning advantage of neural networks with fuzzy logic that represents the human reasoning mechanism. The statistical indicators revealed that the performance of the proposed model is satisfactory.
AB - Bid/no bid decisions are crucial for the business continuity of a contractor. Thus, the decision should be made carefully within the context of the short- and long-term strategy of the organization. Despite the availability of several models, this decision commonly is made based on past experience and subjective judgments. This study aims to show how ANFIS can be used as a decision support tool by contractors during the bid/no bid decision process for international construction projects. Review of the literature revealed that 52 factors may affect a contractor's bid/no bid decision. These factors were categorized into six main groups, which are bidding documents-related factors, contractor-related factors, project-related factors, contract-related factors, host country-related factors, and opportunity-related factors. Having identified these factors, a questionnaire was designed to identify each factor's relative importance. The questionnaire was applied to a large-scale contractor, and actual data from 151 international projects were obtained. An ANFIS model was developed via MATLAB software program using the collected data. The proposed ANFIS model integrates the learning advantage of neural networks with fuzzy logic that represents the human reasoning mechanism. The statistical indicators revealed that the performance of the proposed model is satisfactory.
UR - http://www.scopus.com/inward/record.url?scp=84904625142&partnerID=8YFLogxK
U2 - 10.1061/9780784413517.0111
DO - 10.1061/9780784413517.0111
M3 - Conference contribution
AN - SCOPUS:84904625142
SN - 9780784413517
T3 - Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress
SP - 1083
EP - 1092
BT - Construction Research Congress 2014
PB - American Society of Civil Engineers (ASCE)
Y2 - 19 May 2014 through 21 May 2014
ER -