Abstract
Large construction projects are complex, dynamic, and unpredictable. They are subject to external and uncontrollable events that affect their schedule and financial outcomes. Project managers take decisions along the lifecycle of the projects to align with projects objectives. These decisions are data dependent where data change over time. Simulation-based modeling and experimentation of such dynamic environment are a challenge. Modeling of large projects or multiprojects is difficult and impractical for standalone computers. This paper presents the criteria required in a simulation environment suitable for modeling large and complex systems such as construction projects to support their lifecycle management. Also presented is a platform that encompasses the identified criteria. The objective of the platform is to facilitate and simplify the simulation and modeling process and enable the inclusion of complexity in simulation models.
Highlights
Building a computer simulation model requires specialised knowledge in software engineering and modeling
Similar problems were reported by Mohamed and AbouRizk [32], Centeno and Carrillo [3], and AbouRizk [2]
Simulation platforms lack the services necessary to incorporate decisions and events to emulate the construction projects correctly which might have contributed to hindering the ability to demonstrate the usefulness of simulation to industry professionals
Summary
Building a computer simulation model requires specialised knowledge in software engineering and modeling. Simulation modeling methodologies for construction projects are developed around modeling of repetitive/cyclic operations [2]. Presented in this paper are the criteria used in the development of a simulation environment that is aimed at simplifying the modeling process and facilitating the modeling of construction systems to enable practitioners to use simulation as integrated technology during their project management. We achieve this objective by incorporating agent-based modeling, network modeling, object oriented paradigm, discrete event simulation, Monte Carlo analysis, and distributed calculation in one framework and by integrating simulation models with databases. We focus on presenting and reasoning out the design criteria without addressing the implementation or the detailed possible applications
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