On Using Monte Carlo Simulations for Project Risk Management

2016 ◽  
pp. 150-173
Author(s):  
Cristiana Tudor ◽  
Maria Tudor
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Decision Makers ◽  
Project Schedule ◽  
Project Risk ◽  
Monte Carlo Simulation Technique ◽  
Basic Probability ◽  
The Cost

This chapter covers the essentials of using the Monte Carlo Simulation technique (MSC) for project schedule and cost risk analysis. It offers a description of the steps involved in performing a Monte Carlo simulation and provides the basic probability and statistical concepts that MSC is based on. Further, a simple practical spreadsheet example goes through the steps presented before to show how MCS can be used in practice to assess the cost and duration risk of a project and ultimately to enable decision makers to improve the quality of their judgments.

Monte Carlo Simulation–Based Assessment of Risks Associated with Public–Private Partnership Investments in Toll Highway Infrastructure

2017 ◽  
Vol 2670 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Zhe Han ◽  
Juan Diego Porras-Alvarado ◽  
Jingran Sun ◽  
Zhanmin Zhang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Investment Decision ◽  
Quantitative Information ◽  
Decision Makers ◽  
Control Measures ◽  
Highway Projects ◽  
Monte Carlo Simulation Technique ◽  
Funding Mechanism ◽  
Private And Public

The demands for delivering highway services keep growing worldwide. However, funding from government and public agencies alone cannot cover the capital needed to operate and maintain existing highway systems, much less to construct new ones. Public–private partnerships (PPPs) are an innovative funding mechanism for highway agencies to use private capital and expertise in transportation infrastructure projects so as to increase funding options to bridge the budget gap. Even though parties involved in PPPs take different roles and responsibilities, there are still risks taken or shared by the public and private sectors. In particular, assessing risks associated with the potential returns of investments is of great importance to the private and public sectors. This paper presents a methodological framework for assessing the investment risks of PPP toll highway projects, which may help decision makers. The financial viability associated with the components of a project is considered and analyzed, and the Monte Carlo simulation technique is applied to evaluate the overall project risks. Finally, a numerical case study is conducted to demonstrate the application of the proposed method. The risk analysis provides statistical distribution of investment returns for the project under analysis, which will supply decision makers with direct information to estimate the project’s overall financial risks and develop corresponding risk control measures. The risk simulation results are interpreted so that quantitative information can be provided to agencies to establish investment decision criteria.

The Research of Construction Project Risk Management Based on Monte Carlo Method and Fuzzy Mathematics

2012 ◽  
Vol 442 ◽  
pp. 341-345
Author(s):  
Si Dong Xu ◽  
Xiao Li Cai ◽  
Wei Liu
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Qualitative Analysis ◽  
Quantitative Research ◽  
Construction Project ◽  
Negative Influence ◽  
Fuzzy Mathematics ◽  
Project Risk

A lot of risks of management occur under the process of the construction project, and it will always bring more tremendous negative influence to the project goal. Therefore, there should have the effective risk method for the project superintendent to forecast the risk occurrence and reduce the loss which the risk brings. There are lots of methods about risks management under the process of the construction project at present and most of the method emphasize particularly on qualitative analysis. This article presents a method which base on the knowledge of Monte Carlo Simulation. It will combine the qualitative analysis and quantitative research and puts forward a new solution.

Monte Carlo Simulation for Integrated Cost-Schedule Risk Analysis

2017 ◽  
pp. 29-60 ◽  
Author(s):  
David Todd Hulett
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Project Schedule ◽  
Risk Prioritization ◽  
Simulation Techniques ◽  
Integrated Cost ◽  
Schedule Risk Analysis

Evidence shows that project costs and schedules often overrun their initial plans. The purpose of this chapter is to illustrate the most recent tools and methodologies available today in the application of Monte Carlo simulation techniques to quantify possible overruns in cost and schedule and to understand the sources of those overruns to facilitate risk mitigation actions. Notable methods described include the Risk Driver method, collecting risk data using individual confidential interviews, and use of iterative risk prioritization that facilitates risk focused risk mitigation. Emphasis is placed on the quality of the project schedule and on the quality of the risk data used. The use of prioritization of pre-mitigated for risk mitigation strategies shows how the methodology can be used as a dynamic tool of successful project management.

scholarly journals PROJECT RISK MANAGEMENT USING MONTE CARLO SIMULATION AND EXCEL

2010 ◽  
pp. 362-367
Author(s):  
Wolfgang Tysiak ◽  
Alexander Sereseanu
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Project Risk Management ◽  
Main Task ◽  
It Projects ◽  
Project Risk ◽  
Quantitative Risk Analysis ◽  
Standard Product

In every project, especially in software and IT projects, there is the need to perform an elaborated risk management. One main task that often causes problems is the quantitative risk analysis. In this article we will show how to deal with this by using a well-known standard product: EXCEL.

scholarly journals A DEEPER INSIGHT IN SOME EFFECTS IN PROJECT RISK MANAGEMENT

2014 ◽  
pp. 214-220
Author(s):  
Wolfgang Tysiak
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Program Evaluation ◽  
Project Risk Management ◽  
Time Schedule ◽  
Project Risk ◽  
Popular Approach ◽  
Project Plan

This document shows a possible way how to deal with insecurities in the time schedule of a project plan. It shows that Program Evaluation and Review Technique (PERT), the most popular approach to handle this, bears some severe disadvantages. Furthermore it offers an alternative to overcome them by using Monte Carlo simulation. Finally it can be claimed that a complete change of paradigm is necessary: If you have any insecurities as inputs, everything becomes insecure. This might on the first sight convey the impression that the whole situation converts more complex, but we should rather accept this as the opportunity to apply all the well-known instruments from statistics.

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.

Value-based dentistry: Putting the patient first

2016 ◽  
Vol 7 (3) ◽  
pp. 126-129 ◽  
Author(s):  
Sreenivas Koka ◽  
Galya Raz
Keyword(s):  
Risk Management ◽  
Quality Improvement ◽  
Quality Of Care ◽  
Dental Care ◽  
Time Cost ◽  
Safety Risk ◽  
The Cost ◽  
Over Time

What does ‘value’ mean? In the context of dental care, it can be defined as the quality of care received by a patient divided by the cost to the patient of receiving that care. In other words: V =Q/C, where Q equals the quality improvement over time, which most patients view in the context of the outcome, the service provided and safety/risk management, and C equals the financial, biological and time cost to the patient. Here, the need for, and implications of, value-based density for clinicians and patients alike are explored.

Heuristics as a new way of adjusting the end market value

2021 ◽  
Vol 27 (7) ◽  
pp. 1581-1599
Author(s):  
Semen Yu. BOGATYREV
Keyword(s):  
Behavioral Finance ◽  
Market Value ◽  
Measurement Methods ◽  
Decision Makers ◽  
Emotional Impact ◽  
Psychological Measurement ◽  
Survey Results ◽  
Financial Decision ◽  
The Cost

Subject. The study deals with heuristics as measures of the emotional impact of people who judge about the value and the final result of the valuation. I review ranges of the value variance when influenced by irrational factors. From psychological perspectives, some phenomena are explained with a set of heuristics that exist as part of behavioral finance. Objectives. Referring to the completed studies, I implement elements of behavioral finance, such as heuristics into the method for assessing how financial decision-makers and their emotions influence the value. Methods. The article is based on methods of induction and deduction to process survey results. Results. The article reveals the content of key methods for measuring emotions of financial decision-maker, which conclude on the value, being influenced by heuristics. I demonstrate tools for implementing psychological measurement methods as part of valuation. Conclusions and Relevance. Considering heuristics of value decision-makers, the appraiser and the cost analyst approximate the valuation result to the real conditions, when market actors are irrational. Doing so, they contribute to the quality of the result of appraisal. The findings are applicable to the practice of appraisers, cost analysts, fundamental analysts. Heuristics enrich and expands the classical apparatus of valuation and increases its quality.

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