Evaluation of queuing systems for knowledge-based simulation of construction processes

• Discrete event simulation is widely employed for queuing system modeling using static input data.
• Dynamics of construction queues can be best modeled in data-driven simulations.
• A framework was designed for data modeling of client–server interactions in queues.
• Collected data were mined and extracted knowledge was used to update discrete event simulation models.
• Designed algorithms were validated through experiments using empirical datasets.

During the course of a construction project, there are many situations in which formation of waiting lines or queues is inevitable. The effect of resource delays in queues on the overall project completion time and cost has motivated researchers to employ simulation for analysis of queuing systems in order to identify the best operational strategies to reduce the time wasted in queues. Providing proper and timely input data with high spatial and temporal accuracy for queuing systems simulation enhances the reliability of decisions made based upon the simulation output. Hence, the presented paper describes a methodology for collecting and mining of spatio-temporal data corresponding to the interactions of queue entities to extract computer interpretable knowledge for simulation input modeling. The developed framework was validated using empirical datasets collected from a series of experiments. The extracted relevant knowledge from the queuing system entities was used to update corresponding simulation models.