Notice of Retraction: Construction project schedule risk analysis and assessment using Monte Carlo simulation method

2010 ◽  
Author(s):  
Dezhi Jin ◽  
Zhuofu Wang ◽  
Xun Liu ◽  
Jianming Yang ◽  
Meigui Han
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Construction Project ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Project Schedule ◽  
Schedule Risk ◽  
Schedule Risk Analysis

Analysis of Project Shedule Risk Indexes in PERT Network Using Monte Carlo Simulation

2013 ◽  
Vol 760-762 ◽  
pp. 2205-2211 ◽  
Author(s):  
Yuan Liu ◽  
Zhuo Fu Wang
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Risk Index ◽  
Critical Index ◽  
Project Schedule ◽  
Schedule Risk ◽  
Schedule Risk Analysis ◽  
Construction Schedule

It is convenient and effective to use Monte Carlo simulation (MCS) technique in project schedule risk analysis and assessment, but at the same time, the indexes put forward by scholars up to now is quite few, leaving construction schedule risk assessment still difficult to carry out. Therefore, based on PERT network assumption, the shortcomings of current project schedule risk indexes are summarized and new project schedule risk index is put forward to estimate the criticality of each activity and path to provide more information for project schedule controllers. In the case studied, with the application of the new index, the critical index of each activity is given and divided into five levels, and the new index put forward in this paper shows great superiority over the classic indexes.

SCHEDULE RISK ANALYSIS OF RAILWAY PROJECTS USING MONTE CARLO SIMULATION FOR IMPROVED PROJECT MANAGEMENT

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Motlatso Mabeba ◽  
Jan Harm C Pretorius ◽  
Leon Pretorius
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Road Transport ◽  
Time Frame ◽  
Rail Transport ◽  
Logistics Industry ◽  
The Poor ◽  
Schedule Risk ◽  
Schedule Risk Analysis

Railways have been used throughout history for the transportation of goods. Even though the inception of rail transport improved civilization, due to its inefficiencies, road transport is at present dominating the freight and logistics industry. Company A, which has the largest market share in the rail freight business, has embarked on projects to improve rail efficiencies by moving higher volumes of freight timeously. Most of the projects embarked on by Company A have failed largely due to the poor planning of the projects in the feasibility stages. Most of the planning schedules are overoptimistic and unrealistic making them unreliable and difficult to track. The scope of this study was to investigate the way in which planning schedules of Company A are developed by undertaking a schedule risk analysis on one of the planning schedules titled 'Design of railway exchange yard' and using Monte Carlo simulation to validate the schedule. If projects of Company A can be planned better, using schedule risk analysis, projects can become more successful and completed within the required time frame.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

scholarly journals Integrating Schedule Risk Analysis with Multi-Skilled Resource Scheduling to Improve Resource-Constrained Project Scheduling Problems

2021 ◽  
Vol 11 (2) ◽  
pp. 650
Author(s):  
Muritala Adebayo Isah ◽  
Byung-Soo Kim
Keyword(s):  
Risk Analysis ◽  
Project Scheduling ◽  
Resource Scheduling ◽  
Scheduling Problems ◽  
Project Schedule ◽  
Risk And Uncertainty ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Schedule Risk ◽  
Schedule Risk Analysis

Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.

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