روش های شبیه سازی برای مدیریت هزینه و عملکرد در پروژه های ساخت و ساز در مالزی Simulation techniques for cost management and performance in construction projects in Malaysia

Introduction Cost is one of the most important elements throughout the project life cycle, which can determine the success or failure of a project. High accuracy of cost estimation and control is important to prevent cost overrun at the end of the project (Ali and Kamaruzzaman, 2010). The advancement of computer programs has facilitated the usage of simulation techniques to perform complex mathematical and statistical analyses (Ashworth, 2004). Simulation techniques are used to analyze and assess uncertainties causing issues to project budget. The accuracy of cost estimation can be improved through high level of work definition and risk analysis (Potts and Ankrah, 2014). By using simulation techniques, cost estimator has a better understanding of factors causing cost variance, which enable him/her to make better decision and produce accurate estimation. The detailed cost estimation is converted to a project budget for controlling and monitoring purpose. Project budget or cost baseline is estimated by aggregating the cost of project activities and the cost of contingencies (Norman et al., 2010). Contingencies are included in the budget to respond to anticipated (known) risks at the activities level (Cernauskas and Kumiega, 2008) and to unanticipated (unknown) risks at the project level (Adafin et al., 2014). Project managers and consultants rely on conventional methods to estimate contingencies such as self-experience, intuition, and judgment (Adafin et al., 2014). The usage of traditional techniques of cost estimation may result in over-budgeted or under-budgeted projects. Non-traditional methods such as Monte Carlo simulation, case-based reasoning, neural networks, and multiple regression analysis can be used to forecast cost using probability distribution and improve the accuracy of the estimation (Aram et al., 2014; Kim et al., 2004). However, there is a low uptake of simulation techniques for cost estimation and control in the construction industry (Chou, 2011). Probabilistic estimation is more scientific approach to estimate contingencies but it is seldom used in the construction industry (Uher, 1996). In addition, Akintoye and Fitzgerald (2000) find that complex statistical formula and range estimation (probabilistic technique) are among the least techniques used by contractors for cost estimation in the UK.