Abstract :
Construction projects are one-off endeavors with many unique features such as long period, complicated processes, abominable environment, financial intensity and dynamic organization structures and such organizational and technological complexity generates enormous risks. And environmental and economical dimensions throughout the life cycle of the construction project, so the construction project decision is a difficult and important problem. In this paper, a life cycle engineering (LCE) model is proposed to support construction project decision. The LCE model proposed compares a set of candidate construction projects and, obtained a single indicator for each construction project and for each dimension of evaluation (technical, economic, and environmental), allowing the direct incorporation of the technical, economical and environmental performances into a multi-attribute decision making (MADM) problem. Then, we use the LMS neural network method to solve the MADM problem and get the best construction project from the candidate construction projects.
Keywords :
construction industry; decision making; neural nets; project management; structural engineering computing; LMS neural network method; construction projects; life cycle engineering model; multiattribute decision making; Biological system modeling; Costs; Decision making; Design engineering; Economic indicators; Environmental economics; Least squares approximation; Neural networks; Performance evaluation; Power generation economics; LMS neural network; construction projects; life cycle engineering model; multi-attribute decision making; project management;
