eldo_user

Optimization
Optimization of Sweep Simulations
The extracted measure F is a bidimensional object of size defined by the range of the .STEP
statements. Given the values of the variables x (fixed during each simulation), the simulator
returns a value f = f(x; ω (1) , ω (2) ) for each discretized point (ω (1) , ω (2) ) of the domain Ω.
See also:
• “Global and Local Optimization” on page 629
• “Continuous and Discrete Optimization” on page 630
• “Smooth and Non-Smooth Problems” on page 631
• “Multiple-Run Compatibility” on page 632
Inner and Outer Sweep Parameters
Consider the following minimization problem with respect to the x variable, where the design
parameter ω belongs to the interval Ω = [ω start , ω end ].
A formal circuit formulation example is:
.PARAMOPT X=(XINIT, XL, XU)
.STEP PARAM OMEGA OMEGA_START OMEGA_END OMEGA_INCR
.OBJECTIVE
+ EXTRACT_INFO LABEL=f
+ {$MACRO|FUNCTION}
+ GOAL=MINIMIZE
.OPTIMIZE
The strings XINIT, XL, and XU represent: the initial value of the design variable x, its lower
bound, and its upper bound. Refer to “Specifying Design Variables” on page 596 for more
information.
The example optimization statements can be understood in two different ways:
• The optimizer seeks the smallest value of the function:
such that the value of x is within the interval [x l , x u ]. This case is represented in the right
branch of Figure 13-9. Here the design parameter ω is handled as an inner sweep
parameter.
634
Eldo® User's Manual, 15.3