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Construction simulation is a versatile technique with numerous applications. The basic simulation methods are discrete-event simulation (DES), agent-based modeling (ABM), and system dynamics (SD). Depending on the complexity of the problem, using a basic simulation method might not be enough to model construction works appropriately; hybrid approaches are needed. These are combinations of basic methods, or pairings with other techniques, such as fuzzy logic (FL) and neural networks (NNs). This paper presents a framework for applying simulation for problems within the field of construction. It describes DES, SD, and ABM, in addition to presenting how hybrid approaches are most useful in being able to reflect the dynamic nature of construction processes and capture complicated behavior, uncertainties, and dependencies. The examples show the application of the framework for masonry works and how it could be used for obtaining better productivity estimates. Several structures of hybrid simulation are presented alongside their inputs, outputs, and interaction points, which provide a practical reference for researchers on how to implement simulation to model construction systems of labor-intensive activities and lays the groundwork for applications in other construction-related activities.