Simulation-Based Analysis of Construction Schedule
LI Jing-ru
Abstract
LI Jing-ru
Abstract
This paper presents a simulation-based network plan method aim at overcoming the defects of PERT in planning project schedule with uncertain activityduration.Dynamic simulation of the entire construction process is utilized to obtain the activity durations and project duration.As only basic simulation parameters such as geometrical shape and equipment type are needed the method avoids the difficulty in selection of stochastic function of activity duration in PERT.The construction duration,the completion probability of construction duration,and the critical index of activity are gained by statistical calculation of simulation results.Therefore,the reasonableness of construction duration and critical path are convincing.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper presents a simulation-based network plan method aim at overcoming the defects of PERT in planning project schedule with uncertain activityduration.Dynamic simulation of the entire construction process is utilized to obtain the activity durations and project duration.As only basic simulation parameters such as geometrical shape and equipment type are needed the method avoids the difficulty in selection of stochastic function of activity duration in PERT.The construction duration,the completion probability of construction duration,and the critical index of activity are gained by statistical calculation of simulation results.Therefore,the reasonableness of construction duration and critical path are convincing.
Key concepts: Duration (music), Critical path method, Schedule, Plan (archaeology), Selection (genetic algorithm), Reliability engineering, Computer science, Stochastic simulation