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Cost simulation in an item-based project involving construction engineering and management
Authors:Jui-Sheng Chou
Affiliation:
  • Department of Construction Engineering, National Taiwan University of Science and Technology, 43 Sec.4, Keelung Rd., Taipei, 106, Taiwan
  • Abstract:Despite the extensive use of simulation in management, the continuous simulation model for cost estimation remains unexploited, especially for construction engineering and management. This study introduces streamlining Monte Carlo simulation procedures with evaluation of stochastic processes and input probability distribution selection via hypothesis testing, and specification of correlations between simulated variates. By using self-developed algorithms and a spreadsheet-add-on program, this investigation uses historical construction projects as case study data to create an early-stage cost distribution for budget allocation. While establishing the applicability of the proposed simulation procedures, this study demonstrates that the simulated cost results present superior simulation accuracy in addition to separating the principal work items and unit price component model. Generally, the precision and absolute error rates fall into acceptable ranges when the proposed systematic simulation procedures are adopted. The cost simulation approach offers a simplified decision tool for fairly assessing construction cost and uncertainties based on the experienced judgment of project managers.
    Keywords:BCIS, Building Cost Information Service   CDF, cumulative distribution function   K-S, Kolmogorov-Smirnov   LCGs, linear congruential generators   MAPE, mean absolute percentage error   MCS, Monte Carlo simulation   MLNRS, multivariate lognormal random simulation   MNRS, multivariate normal random simulation   MPE, mean percentage error   NORTA, NORmal To Anything   NTD, New Taiwan Dollar   PC, Pearson's Chi-square   PDF, probability density function   PEM, probabilistic estimation method   PWI, principal work items   RICS, Royal Institute of Chartered Surveyors   SBS, stochastic budget simulation   SD, standard deviation   SDPE, standard deviation percentage error   TPC, total project cost derived by summing work items costs   TPCS, total project cost derived from sum of item quantity multiplied by unit price
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