Study On The Application Of Random Simulation Method In Bidding Price Decision-Making

Aimed at the situation which employer is much more than contractor, the bidder must make a most competitive price in the process of bidding if he wants to seek survival and development in the furious market competition. The bidder will lose the opportunity of winning bid with high price, whereas he may lose the deserved profit or even a loss situation. Therefore, how to determine a appropriate price is the key to bidding price decision-making. From theoretical research and empirical analysis, this paper forms theory and specific method of bidding price decision-making based on random simulation.In theoretical research, the paper firstly introduces the cost of Bill of Quantities, and then makes a comparison between list price and fixed price, shows the merits of list price and the coping strategies of the bidder. Subsequently, combined with the general procedures of bidding, the paper analyses the factors of affecting the bidding from cost and profit and points out that the bidder should select strategies combined with business objectives. Next the paper introduces the basic antilogy of random simulation, calculated steps and the selection of the type of bidding distribution.In the part of modeling, the paper gives principles about modeling: bidding price based BOQ and comprehensive evaluation method. From the analysis of rivals' historical date, the paper discusses the known and unknown opponents according to the date's level of detail. Being dead against unknown opponents, brings forward a fuzzy clustering analysis method to classify the unknown competitors based on the fuzzy equivalent matrix, according to the degree of similarity between the known and unknown opponents, replaces unknown opponents' data with known opponents'. By the statistical analysis and testing of historical data, the bidder can get the distribution function and generate random date by computer . In accordance with the specific evaluation method in the tender documents the bidder can get a price range or a figure in which the bidder can get higger score and then enhance the probability of winning bid.Finally, selecting a construction company's bidding data, the paper gets the price of hightest probability of winning bid by stochastic simulation and provides basis for decision-making. The specific example testifies the practicality of the method and the effectiveness of the simulation result.