Stochastic construction time-cost trade-off analysis

Traditional time-cost trade-off analysis assumes that the time and cost of an option within an activity are deterministic. However, in reality the tim e and cost are uncertain. Therefore, in analyzing the time-cost trade-off p roblem, uncertainties should be considered when minimizing project duration or cost. Simulation techniques are useful for analyzing stochastic effects , but a general strategy/algorithm is needed to guide the analysis to obtai n optimal solutions. This paper presents a hybrid approach that combines si mulation techniques and genetic algorithms to solve the time-cost trade-off problem under uncertainty. The results show that genetic algorithms can be integrated with simulation techniques to provide an efficient and practica l means of obtaining optimal project schedules while assessing the associat ed risks in terms of time and cost of a construction project. This new appr oach provides construction engineers with a new way of analyzing constructi on time/cost decisions in a more realistic manner. Historical time/cost dat a and available options to complete a project can be modeled, so that const ruction engineers can identify the best strategies to take to complete the project at minimum time and cost. Also, what-if scenarios can be explored t o decide the desired/optimal time and/or cost in planning and executing pro ject activities.