Evaluation of queuing systems for knowledge-based simulation of construction processes |
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| Affiliation: | 1. Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais 1, 1049-001 Lisboa, Portugal;2. ICIST, Instituto de Engenharia de Estruturas, Território e Construção, DECivil, Departamento de Engenharia Civil, Arquitetura e Georecursos, Avenida Rovisco Pais 1, 1049-001 Lisboa, Portugal;3. INOV INESC INOVAÇÃO, Instituto de Novas Tecnologias, Rua Alves Redol, 9, 1000-029 Lisboa, Portugal;1. Dept. of Architectural Engineering, Gyeongnam National University of Science and Technology, 33, Dongjin-ro, Jinju-si, Gyeongsangnam-do, 52725, South Korea;2. Department of Construction Science, Texas A&M University, 3137 TAMU, College Station, TX 77843-3137, United States;3. Dept. of Civil Engineering, University of Nebraska–Lincoln, N104 Scott Engineering Center, Lincoln, NE 68588, United States;4. Dept. of Civil and Environmental Engineering, Univ. of Michigan, 2350 Hayward St., Ann Arbor, MI 48109, United States;1. Building, Civil and Environmental Engineering Department, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec H3G 1M8, Canada;2. Concordia Institute for Information Systems Engineering, 1455 De Maisonneuve Blvd. West, Montreal, Quebec H3G 1M8, Canada;3. Concordia Institute for Information Systems Engineering, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec H3G 1M8, Canada;1. School of Civil and Environmental Eng., UNSW, Kensington, NSW, Australia;2. Department of Civil Engineering, Universidad Tecnica Federico Santa Maria, Valparaiso, Chile |
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| Abstract: | 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. |
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