Bid/no-bid decision-making using rough sets and neural networks

Authors:
Huawang Shi
Affiliations:
School of Civil Engineering, Hebei University of Engineering, Handan, P.R.China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

One of the most important decisions that have to be made by contractor firms is whether to bid or not to bid for a project, when an invitation has been received. For any construction company, being able to deal successfully with various bidding situations is of crucial importance, Especially in today's highly competitive construction market. The frame work presented in this study integrated methodology of rough set (RS) and artificial neural network (ANN) will serve as a basis for a knowledge-based system model which will guide the contracting organizations in reaching strategically correct bid/no bid and make decisions. Using rough sets, we can get reduced information table, which implies that the number of evaluation criteria such as reputation of company and risks of project is reduced with no information loss through rough set approach. And then, this reduced information is used to develop classification rules and train neural network to infer appropriate parameters. The proposed decision support system framework are of good value to contracting organizations in different construction markets.