Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 11 results ...
Agbulos, A, Mohamed, Y, Al-Hussein, M, AbouRizk, S and Roesch, J (2006) Application of Lean Concepts and Simulation Analysis to Improve Efficiency of Drainage Operations Maintenance Crews. Journal of Construction Engineering and Management, 132(03), 291–9.
El Wardani, M A, Messner, J I and Horman, M J (2006) Comparing Procurement Methods for Design-Build Projects. Journal of Construction Engineering and Management, 132(03), 230–8.
El-Diraby, T E (2006) Web-Services Environment for Collaborative Management of Product Life-Cycle Costs. Journal of Construction Engineering and Management, 132(03), 300–13.
Ellis, R D and Lee, S (2006) Measuring Project Level Productivity on Transportation Projects. Journal of Construction Engineering and Management, 132(03), 314–20.
Hinze, J, Devenport, J N and Giang, G (2006) Analysis of Construction Worker Injuries That Do Not Result in Lost Time. Journal of Construction Engineering and Management, 132(03), 321–6.
Kaiser, M J (2006) Offshore Decommissioning Cost Estimation in the Gulf of Mexico. Journal of Construction Engineering and Management, 132(03), 249–58.
Lee, D and Arditi, D (2006) Automated Statistical Analysis in Stochastic Project Scheduling Simulation. Journal of Construction Engineering and Management, 132(03), 268–77.
- Type: Journal Article
- Keywords: Critical path method; Probability; Simulation; Statistics; Scheduling; Construction management;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:3(268)
- Abstract:
This paper describes a stochastic simulation-based scheduling system (S3) that: (1) integrates the deterministic critical path method (CPM), the probabilistic program evaluation and review technique (PERT), and the stochastic discrete event simulation (DES) approaches into a single system and lets the scheduler make an informed decision as to which method is better suited to the company’s risk-taking culture; (2) automatically determines the minimum number of simulation runs in DES mode and therefore optimizes the simulation process; and (3) provides a terminal method that tests the statistical significance of the differences between simulations, hence eliminating outliers and therefore increasing the accuracy of the DES process. The system is based on an earlier version of the system called stochastic project scheduling simulation and makes use of all the capabilities of this system. The study is of value to practitioners because S3 produces a realistic prediction of the probability of completing a project in a specified time. The study is also of relevance to researchers in that it allows researchers to compare the outcome of CPM, PERT, and DES under different conditions such as different variability or skewness in the activity duration data, the configuration of the network, or the distribution of the activity durations.
Soetanto, R, Dainty, A R, Glass, J and Price, A D (2006) Empirical Evaluation of Structural Frame Performance Criteria: Realizing the Potential of Hybrid Concrete Construction. Journal of Construction Engineering and Management, 132(03), 278–90.
Tang, W, Duffield, C F and Young, D M (2006) Partnering Mechanism in Construction: An Empirical Study on the Chinese Construction Industry. Journal of Construction Engineering and Management, 132(03), 217–29.
Wibowo, A (2006) CAPM-Based Valuation of Financial Government Supports to Infeasible and Risky Private Infrastructure Projects. Journal of Construction Engineering and Management, 132(03), 239–48.
Zhang, H, Li, H and Tam, C M (2006) Particle Swarm Optimization for Preemptive Scheduling under Break and Resource-Constraints. Journal of Construction Engineering and Management, 132(03), 259–67.