# optimize Method

Performs an optimization on the model.

- First create the optimizer with the problem definition.
- Second, instruct the optimizer to optimize the specified system to a desired accuracy.

## Example

```
def optimize (self):
# Define the cost functions in a list – there are 3 of these
obj = [self.a2x, self.a2y, self.a2psi]
# Define the weights for the cost functions in a list – there are 3 of these
wt = [1,1,1]
# Define the list of responses consist of inequality constraints – there are 6 of these
ineq = [self.cons1, self.cons2, self.cons3, self.cons4, self.cons5, self.cons6]
# Create the optimizer
opt = Optimizer ( label = "Optimize RMS2", # Label
objective = obj, # Objectives
weights = wt, # Weights
type = "KINEMATICS", # Simulation Type
end = 2, # End Time
dtout = 0.01, # No. of steps
plot = True, # Display plots
ineqConstraints = ineq # Inequality constraints
)
# Now perform the optimization
x = opt.optimize ()
# Return the result
return x
```

## Example

```
def optimize (self):
# Define the cost functions in a list – there are 3 of these
obj = [self.a2x, self.a2y, self.a2psi]
# Define the weights for the cost functions in a list – there are 3 of these
wt = [1,1,1]
# Create the optimizer
opt = Optimizer ( label = "Optimize RMS2", # Label
objective = obj, # Objectives
weights = wt, # Weights
simMethod = self.simulate # The simulation method
plot = True, # Display plots
)
# Now perform the optimization
x = opt.optimize (accuracy=1e-3)
# Return the result
return x
```