Optimization
and risk analysis
You have two simulation
types to choose between:
Simulation and
Risk Analysis. Simulation is the traditional way
of running your simulation, one run at a time. Risk Analysis, on
the other hand, allows you to include uncertainty in your simulation
by assigning probability distributions to the assumptions you have
made for your model. Studio will use advanced sampling methods to
analyze how sensitive your model is to changes in these assumptions.
The new
Optimize tool uses advanced
goal-seeking methods to find the best set of decisions that fulfill
the goals you have set. The tool can be used in both of the simulation
types above, allowing you to optimize your model both with and without
risk.
You can create
Analysis Variables on any simulation. For ordinary
simulations, you can define assumptions, decisions and objectives,
while effects are available for risk analyses.
In a risk analysis, assumptions can be defined as probability distributions,
allowing you to introduce uncertainty into your simulation. Analysis
variables may be cloned, allowing you to create sequences of analysis
variables with different apply times, for the same model variable.
By combining these various tools and features, you can run a number
of useful analyses on your simulation. The various analyses are
described in the next sections.
Scenario control and optimization
Scenario control
By using decision and assumption analysis variables with ordinary
simulation runs, you can program scenarios for your simulation runs.
Decisions may also be used to control when the simulation user is
allowed to provide input for the simulation, and they also allow
you to make decisions for the entire simulation
run in advance.
This automated simulation control is available by adding
Analysis Variables to a Simulation,
and then clicking
Play.
Optimization
Powersim Studio automates the search for optimal decisions, saving
you a lot of time and increasing the chances of finding the optimal
solution. You are even allowed to specify mulitple objectives, and
assign importance to each of them. This
way you can make tradeoffs between conflicting goals.
Studio automatically serarches for decisions that produce the best
results possible. It finds optimal values for decisions and computes
a measure for the distance between simulated results and specified
objectives. To optimize a policy, Studio needs to know which policy
input values and decisions it can vary
in order to reach one or more objectives that you have specified.
In addition you can specify assumptions about other factors that
influence the performance of your system.
Optimization is available by adding
Analysis Variables to a
Simulation, and then invoking the
Optimize tool.
Risk assessment and risk management
Risk Assessment
Factors that are external to your organization, such as the inflation
rate or other values that are difficult to determine or control,
represent risk factors if they seriously
affect the results. These are are called assumptions in the model.
Through the risk assessment analysis you can investigate what effects
uncertainties in assumptions have on the results. This task finds
the probability distributions for the simulated results, based on
the specified uncertainties of the assumptions.
You can also use this analysis to find variables that are leverage
points for improving performance.
Risk A ssessment is available by adding
Analysis Variables to a
Risk Analysis, and then clicking
Play.
Risk Management
If you have established that your model is sensitive to changes
in certain risk factors, you should take them into account when
optimizing your policy. Otherwise, the chances of achieving your
objectives with a particular policy may be rather low. Through the
Risk Management analysis you can find decisions that make
your model produce good and robust results. It assures that objectives
will be with with a certain level of confidence.
Risk Management is available by adding
Analysis Variables to a
Risk Analysis, and then invoking the
Optimize tool.
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