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. 1. Introduction Building a computer simulation model requires specialised knowledge in software engineering and modeling. Modifications to models are difficult to implement. Simulation is generally regarded by professionals in the construction industry as an additional layer to the business software environment. Feedback from industry practitioners and simulation researchers shows that minimizing the specialized knowledge and simplifying the modeling process are necessary to increase the appeal to simulation [1]. Simulation modeling methodologies for construction projects are developed around modeling of repetitive/cyclic operations [2]. Such models are small compared to those required to model a complete construction project. Projects are data dependent where data are updated periodically by actualizing the data of completed work and reforecasting future work. Models should be current with latest data. Projects are managed by people who influence the project outcomes by their decisions. Projects are also affected by external and internal events that could change their schedule and financial results. Neglecting the inclusion of decisions and events in the model results in unrealistic project forecast. 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
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