Codecamp Iasi 7 mai 2011 Monte Carlo Simulation

26 October 2010 Monte Carlo Simulation Constantinescu Eugen

Index
Motivation and objectives
Basic Knowledge
Practical examples
Conclusions
Reference Links

Motivation and objectives
Motivation:
Our estimations from projects are not good enough
There is place for risks assessment improvement
This model is closer to reality than the classical one
Let's try to see our projects from more points of view
Objectives:
Learn about the basic knowledge MCS
What are the main benefits from using MCS?
What we can change?
Where we can improve?

Basic knowledge
Process determinist versus process stochastic
Monte Carlo Simulation is a method for iteratively evaluating a deterministic model using sets of random numbers as inputs. This method is often used when the model is complex, nonlinear, or involves more than just a couple uncertain parameters.

Basic knowledge
Step 1: Create a parametric model , y = f (x1, x2, ..., x q ).
Step 2: Generate a set of random inputs , x i 1, x i 2, ..., x iq .
Step 3: Evaluate the model and store the results as y i .
Step 4: Repeat steps 2 and 3 for i = 1 to n .
Step 5: Analyze the results using histograms, summary statistics, confidence intervals, etc.

Basic knowledge
Histograms
Data:
Frequency
Cumulative frequency
Min, Mean (Average), Max
Skewness
Kurtosis
Confidence Interval

Practical examples
1.MSP small example
MCS sheets
Analysis
2.MSP real life example
MCS sheets
Analysis

Conclusions
Learn about the basic knowledge MCS – DONE  Take a look over the MATH behind MCS, or just go to point 2.
What are the main benefits from using MCS?
CP and PERT (Program Evaluation and Review Technique) are optimistic estimations => MCS helps for a better planning
What we can change?
We should focus on the tasks which have highest chance to become CP.
We should start to change the current estimation template and MSP template so that we can include Min, Most Likely and MAX estimation values.

Conclusions
Where we can improve? Identify and define the risks easier ( Assessing Risks Improvement ) Analyze the tasks which have higher impact into the project costs ( See the most sensitive tasks)

Reference Links
http://www.vertex42.com/ExcelArticles/mc/MonteCarloSimulation.html
http://mathworld.wolfram.com/MonteCarloMethod.html
http://rule-of-thumb.net/monte-carlo-simulation-for-ms-project/ http://sourceforge.net/projects/montecarloprj/
file://storage/IIC-ForAll/08_PM_Community/MCS

Codecamp Iasi 7 mai 2011 Monte Carlo Simulation

by CodeCamp/Iasi on May 11, 2011

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Codecamp Iasi 7 mai 2011 Monte Carlo Simulation — Presentation Transcript