Optimization of completion schedule forecasting in case study of double-double track development project (Package A) using the probabilistic pert method

Leni Sagita Riantini, Mohammad Ichsan, Bambang Trigunarsyah, Ayomi Dita Rarasati, Nuraziz Handika, Chrys Adrian Lolo

Research output: Contribution to journalArticlepeer-review

Abstract

This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

Original languageEnglish
Article number7798
JournalJournal of Infrastructure, Policy and Development
Volume8
Issue number9
DOIs
Publication statusPublished - 2024

Keywords

  • Monte Carlo simulation
  • quantitative risk
  • railway infrastructure
  • scheduling

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