Modeling Framework and Architecture of Hybrid System Dynamics and Discrete Event Simulation for Construction

: Construction system modeling aims to improve construction work performance by tracking the dynamic behaviors of construction systems. More accurate system modeling can be achieved by considering the mutual effects of construction operations on the context level of the system. Hybrid models of discrete event simulation (DES) and system dynamics aim to capture these mutual effects to provide model developers with more precise system analysis. Although system dynamics models are used to capture the behavior of the system at the context level, DES models are utilized to capture construction operations. The potential benefits of utilizing hybrid models for complex systems have been argued and established, but there are still limited studies that have utilized this modeling approach for real construction systems. In this research, we have attempted to identify the challenging issues that have caused this problem and to confront this problem by proposing a hybrid framework and architecture, which address these challenges. To verify the effectiveness of the new model, the performance of the proposed hybrid modeling framework and architecture has been tested by applying the proposed model in a real-scale construction-related system.

[1]  Asim Karim,et al.  CONSCOM: An OO Construction Scheduling and Change Management System , 1999 .

[2]  Bernard P. Zeigler,et al.  Quantization-based filtering in distributed discrete event simulation , 2002, J. Parallel Distributed Comput..

[3]  Albert T. Jones,et al.  Enterprise simulation: a hybrid system approach , 2005, Int. J. Comput. Integr. Manuf..

[4]  Albert T. Jones,et al.  Hierarchical production planning using a hybrid system dynamic-discrete event simulation architecture , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[5]  Simaan M. AbouRizk,et al.  Modeling architecture for hybrid system dynamics and discrete event simulation , 2009 .

[6]  Erwin Fehlberg,et al.  Klassische Runge-Kutta-Formeln vierter und niedrigerer Ordnung mit Schrittweiten-Kontrolle und ihre Anwendung auf Wärmeleitungsprobleme , 1970, Computing.

[7]  Feniosky Peña-Mora,et al.  Strategic-Operational Construction Management: Hybrid System Dynamics and Discrete Event Approach , 2008 .

[8]  Vineet R. Kamat,et al.  Algorithm for Accurate Three-Dimensional Scene Graph Updates in High-Speed Animations of Previously Simulated Construction Operations , 2009, Comput. Aided Civ. Infrastructure Eng..

[9]  Ioana Rus,et al.  Software process simulation for reliability management , 1999, J. Syst. Softw..

[10]  Doo-Hwan Bae,et al.  An approach to a hybrid software process simulation using the DEVS formalism , 2006, Softw. Process. Improv. Pract..

[11]  Miroslaw J. Skibniewski,et al.  Simulation of Accuracy Performance for Wireless Sensor-Based Construction Asset Tracking , 2009, Comput. Aided Civ. Infrastructure Eng..

[12]  Vladimir L. Kharitonov,et al.  Distributed simulation of hybrid systems with AnyLogic and HLA , 2002, Future Gener. Comput. Syst..

[13]  SangHyun Lee,et al.  Integrating Construction Operation and Context in Large-Scale Construction Using Hybrid Computer Simulation , 2009 .

[14]  David Raffo,et al.  Application of a hybrid process simulation model to a software development project , 2001, J. Syst. Softw..

[15]  Seokho Chi,et al.  A Methodology for Object Identification and Tracking in Construction Based on Spatial Modeling and Image Matching Techniques , 2009, Comput. Aided Civ. Infrastructure Eng..

[16]  Hojjat Adeli,et al.  Scheduling/Cost Optimization and Neural Dynamics Model for Construction , 1997 .