Abstract: Modeling and analyzing construction operations using simulation techniques allows researchers to capture the uncertainty and randomness usually associated with these operations and can thus be an effective tool for analysis ...

Abstract: Formal stochastic simulation study has been recognized as a remedy for the shortcomings inherent to classic critical path method (CPM) project evaluation and review technique (PERT) analysis. An accurate and efficient ...

Abstract: This paper discusses the derivation of a probabilistic neural network classification model and its application in the construction industry. The probability inference neural network (PINN) model is based on the same concepts ...

Abstract: The back-propagation neural network (BPNN) has been researched and applied as a convenient decision-support tool in a variety of application areas in civil engineering. However, learning algorithms such as the BPNN do not ...

Abstract: Range estimating is a simple form of simulating a project estimate by breaking the project into work packages and approximating the variables in each package using statistical distributions. This paper explores an alternate ...

Abstract: This paper proposes a framework for simulating weather-sensitive construction projects that are executed under extreme weather conditions. It applies the framework steps to enable simulating and planning pipeline construction ...

Abstract: A utility theory model, which is one of three generic methods for bid markup determination, is developed using 21 criteria in the bidding decision. The majority of the criteria are evaluated subjectively by a decision ...