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AbouRizk, S M and Wales, R J (1997) Combined Discrete-Event/Continuous Simulation for Project Planning. Journal of Construction Engineering and Management, 123(01), 11–20.

Crowley, L G (1997) Robust Statistical Estimators for Use within Competitive Bid Data. Journal of Construction Engineering and Management, 123(01), 53–63.

Daoud, O E K (1997) The Architect/Engineer's Role in Rehabilitation Work. Journal of Construction Engineering and Management, 123(01), 1–5.

Elazouni, A M (1997) Constructability Improvement of Steel Silos during Field Operations. Journal of Construction Engineering and Management, 123(01), 21–25.

Everett, J G and Farghal, S H (1997) Data Representation for Predicting Performance with Learning Curves. Journal of Construction Engineering and Management, 123(01), 46–52.

Farghal, S H and Everett, J G (1997) Learning Curves: Accuracy in Predicting Future Performance. Journal of Construction Engineering and Management, 123(01), 41–45.

Kangari, R and Miyatake, Y (1997) Developing and Managing Innovative Construction Technologies in Japan. Journal of Construction Engineering and Management, 123(01), 72–78.

Kartam, S, Ballard, G and Ibbs, C W (1997) Introducing a New Concept and Approach to Modeling Construction. Journal of Construction Engineering and Management, 123(01), 89–97.

Mondorf, P E, Kuprenas, J A and Kordahi, E N (1997) Segmental Cantilever Bridge Construction Case Study. Journal of Construction Engineering and Management, 123(01), 79–84.

Russell, J S, Jaselskis, E J and Lawrence, S P (1997) Continuous Assessment of Project Performance. Journal of Construction Engineering and Management, 123(01), 64–71.

Shi, J and AbouRizk, S M (1997) Resource-Based Modeling for Construction Simulation. Journal of Construction Engineering and Management, 123(01), 26–33.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1997)123:1(26)
  • Abstract:
    The application of simulation in the construction industry has always been hindered by the complexities involved in constructing simulation models and the resultant time requirement. This paper presents a modeling method for construction simulation—resource-based modeling (RBM), in which operating processes of active resources are defined as atomic models (basic and unique description of a particular process) and are stored in a model library. These atomic models can be modified to form project-specific atomic models according to user-specified project information. Through defined linking structures, they can be assembled into a working simulation model for the project. Therefore, the user can construct a simulation model for a project by simply specifying required resources and project site conditions. The modeler does not have to be proficient with simulation theory and the selected simulation language. Our experience with implementing simulation in the construction industry shows that this is an effective approach. A sample application is used to illustrate the RBM concepts and its advantages.

Songer, A D and Molenaar, K R (1997) Project Characteristics for Successful Public-Sector Design-Build. Journal of Construction Engineering and Management, 123(01), 34–40.

Tiong, R L K and Alum, J (1997) Final Negotiation in Competitive BOT Tender. Journal of Construction Engineering and Management, 123(01), 6–10.

Touran, A, Sheahan, T C and Ozcan, E (1997) Rational Equipment Selection Method Based on Soil Conditions. Journal of Construction Engineering and Management, 123(01), 85–88.