earticle

영어

This paper introduces a system called Simulation-based Stochastic Bidding Cost Estimation System (S2BC) that use simulation modeling and analysis technique. It better represents the real world system involved in construction bidding.
The prediction accuracy was compromised because of the assumptions which existing models have adopted. However, The S2BC complements the lack of accuracy. Historical bidding data obtained from the Korea National Housing Corporation was used to validate the method. Bidding projects in the Historical DB were selected by random sampling. The ration of bidding let was calculated using the occurrence of participants who entered into a specific bidding. On the assumption that bidding pattern retained on the historical DB has reproducibility, the probability of winning was computed using the cumulative probability distribution that is obtained from the user defined numbe r of random sampling of bidding projects out of the Historical DB. The existing computation, which is handled by means of deterministic procedure, was converted into stochastic model using simulation modeling and analysis technique. The best fitted probability distribution function is estimated using the historical data. The reliability of estimating probability of winning on specified bidding let is improved using the S2BC.