An integrated simulation model for construction

doi:10.1016/0928-4869(95)00018-6

Simulation Practice and Theory

Volume 3, Issue 6, 15 January 1996, Pages 401-420

https://doi.org/10.1016/0928-4869(95)00018-6 Get rights and content

Abstract

Systems simulation has proven to be an effective tool in the analysis of various manufacturing operations. Simulation has also found its way to construction as a means for project planning and control as well as for operation analysis. It was found especially useful for project managers in determining the impact of various factors upon the construction schedule. Weather, for example, influences the duration of many construction activities thereby causing uncertainty in the project schedule. This paper presents a simulation application where the authors have developed a combined simulation model that integrates many methods required for the successful application of simulation in modeling complex projects such as those encountered in construction. The methodology implemented includes using a general purpose simulation language where the user can extend the functionality of the system by writing his own code, developing the required methods for stochastically generating the occurrence of weather variables for use in project simulation studies, and estimating productivity using artificial intelligence.

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Non-parametric weather generator for modelling construction operations: Comparison with the parametric approach and evaluation of construction-based impacts
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Citation Excerpt :
For instance, Richardson [17] used the exponential distribution function, fn(x) = λn exp (− λn x), for its simplicity, but stated that mixed exponential, fn(x) = an exp (− bnx) + cn exp (− dnx), and gamma distribution functions are better at describing amounts of precipitation. Wales and AbouRizk [9] and Shahin [13] used a two-state gamma distribution because of its flexibility in using two parameters to describe the distribution. A full description of the construction of parametric weather generators can be found in Shahin [13].
Weather generators are frequently used to provide a realistic environment to model weather-sensitive construction operations. Although a parametric weather generation approach is commonly used to construct such generators, this approach is associated with drawbacks such as the assumption that weather variables are normally distributed. In this paper, a simplified weather generation approach, based on the bootstrap technique, is proposed. An experiment comparing both approaches is conducted. A three-stage model evaluation has been applied to outputs from both generators. The evaluation includes: (1) an evaluation of both generators' assumptions, (2) a comparison of both generators' outputs with historical records, and (3) an evaluation of imperfection effects associated with the generators' outputs when applied on weather-sensitive construction models. Results indicate that although both generators are reliable for generating daily synthetic weather series and in modelling construction operations, non-parametric weather generators demonstrate a better performance when modelling time-scale flexibility (hourly/daily) in construction operations.
Adaptive real-time tracking and simulation of heavy construction operations for look-ahead scheduling
2012, Automation in Construction
Citation Excerpt :
Optionally, to further improve forecasting accuracy, certain uncertainty variables – e.g., weather and staffing level and their impacts on simulation input – can be modeled explicitly using a prediction model. For example, Wales and AbouRizk [17] developed a continuous-change weather process model and combined it with a simulation-based project critical path method network. The impact of weather conditions on activity durations is modeled by neural network models.
This paper proposes an adaptive real-time tracking and simulation of heavy construction operations for look-ahead scheduling during construction field operations. In this method, construction operation data are constantly captured using tracking sensors and the data is then fed into a simulation model for automatic model updating. This adaptive capability allows a pre-defined simulation model to be constantly updated to reflect the changing project environment for more accurate look-ahead scheduling. Compared with the traditional offline simulation that uses stationary inputs, the capability of the proposed real-time simulation to dynamically incorporate new project data and adapt to changes in field operations can improve the accuracy of project look-ahead scheduling. A prototype system and case studies are presented to demonstrate the feasibility of the proposed concept.
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An integrated simulation model for construction

Abstract

Simulation model to forecast project completion time

J. Constr. Engrg. Mngmt.

Simulating effects of weather on construction

J. Constr. Engrg. Mngmt.

Generating random variates from gamma distributions with noninteger shape parameters

Simulation of construction project duration

J. Constr. Div.

Sampling from the gamma distribution on a computer

Comm. ACM

CYCLONE: Method for modeling of job site processes

J. Constr. Div.

Precedence and Arrow Networking Techniques for Construction

Probabilistic models

A first order nonhomogeneous Markov chain for the daily rainfall occurrences

Mathematical assessment of synthetic hydrology

Water Resources Res.