What is Monte Carlo Simulation? How does it work?

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What is Monte Carlo Simulation? How does it
work?
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• As the name suggests, it seems exciting to know
  what Monte Carlo simulation is. The term Monte
  Carlo simulation has its charisma, it sounds
  complicated. But in reality, its not complicated
  as we think. Lets see if we can nail down the
  entire process in straightforward terms.
• Risk analysis is a part of every decision we make
  in construction projects. We continuously face
  uncertainty and variability, and we always have
  new access to information that cannot accurately
  predict the future. Monte Carlo simulation, also
  known as Monte Carlo method allows you to see all
  the possible consequences of your decisions and
  evaluate the impact of risk, allowing for better
  decision making under uncertainty.

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What is Monte Carlo Simulation?

• In a straightforward language, Monte Carlo is the
  easiest way to understand how the inputs into a
  system may affect the outputs.
• Monte Carlo simulation is a computerized
  mathematical technique that allows people to
  calculate risk in decision making and
  quantitative analysis. The method is widely used
  by the professionals in fields like project
  management, manufacturing, engineering, research,
  and development, etc.
• Monte Carlo enables the decision-maker with a
  range of possible outputs and the probabilities
  that will occur for any choice of action.
• The technique was first used by scientists
  working on the atom bomb and thus named as Monte
  Carlo, the Monaco resort town famous for its
  casinos. The simulation has also been used to
  model diversified physical and conceptual
  systems.

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• Lets take an example here, lets say you have
  coins put on a table. You count tails and heads
  and come up with a ratio that you plot on a
  graph. You then perform the same experiment 1000
  times to see what the results and the chart look
  like. The entire process is Monte Carlo method.
  Now, if you programmed a computer to model the
  same process and ran the model 1000 times or
  more, the end graphing you get is termed as Monte
  Carlo simulation.

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How does Monte Carlo Simulation Work?

• Monte Carlo simulation performs risk analysis by
  building models of potential results, and also by
  replacing a range of values for any factor that
  has an integral uncertainty. It then evaluates
  results over and over, each time using a
  different set of random values from probability
  functions, depending upon the number of risks and
  the ranges defined for them. A Monte Carlo could
  involve thousands or more recalculations before
  they are complete.
• A Monte Carlo simulation provides distribution of
  possible outcome values. By using probability
  distributions, variables can also have different
  assumptions about different outcomes that are
  occurring. The probability distributions are a
  more realistic way of describing uncertainty in
  variables of a risk analysis.

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Benefits of Monte Carlo Simulations

• A Monte Carlo simulation furnishes a projects
  decision-maker with a scope of possible results,
  and also the probabilities of each outcome that
  might take place. A Monte Carlo simulation
  provides some advantages as follows
• Probabilistic Results In this, the result not
  only shows what could happen but how likely each
  outcome is to occur.
• Graphical Results With the data generated by
  Monte Carlo simulation, it is facile to create
  graphs of different outcomes. Their chances of
  occurrence become significant for communicating
  findings to the other involved stakeholders.
• Sensitivity Analysis In the Monte Carlo
  simulation, it is easy to see which inputs have
  the most significant effect on bottom-line
  results.
• Scenario Analysis Using Monte Carlo simulation,
  the analysts can exactly see which inputs had
  what values together when a particular outcome
  occurs.