Abstract
During a construction project, the cost of progress is the most important factor affecting the profitability of the project. It would be beneficial to the contractor to have prior knowledge concerning the cost of progress of a project. This study uses case-based reasoning (CBR) to predict the cost of progress in order to develop appropriate strategies. This study also investigates genetic algorithms (GAs) for weight generation and applies them to a real project case. To achieve the objective, quantitative data have been collected from real completed construction projects. The proposed prediction system, namely EVAS-CBR-GAs, was then performed on the identified influential variables. The results show that the presented methodology can consistently reduce errors and potentially be useful for owners and contractors in the early financial planning stage. Recognizing this need, the author has developed a comprehensive system for planning and controlling the cost of contractor progress.
