User Guide

Advanced Options 4
-19
Choosin
g
an Optimization
Method for Sin
g
le Goal
Problems (Least Squares/
Minimization Options)
The PSpice Optimizer implements two general classes of
algorithm to measure design performance: least squares and
minimization. These algorithms are applicable to both
unconstrained and constrained problems.
Least squares
A reliable measure of performance for a
design with multiple targets is to take the deviation of each
output from its target, square all deviations (so each term is
positive) and sum all of the squares. The PSpice Optimizer then
tries to reduce this sum to zero.
This technique is known as least squares. Note that the sum of
the squares of the deviations becomes zero only if all of the
goals are met.
Minimization
Another measure of design performance
considers a single output and reduces it to the smallest value
possible.
Example: Power or propagation delay, each of which is a
positive number with ideal performance corresponding to zero.
Choosin
g
the al
g
orithm
When optimizing for more
than one goal, the PSpice Optimizer always uses the least-
squares algorithm. For a single goal, however, you must specify
the algorithm for the optimizer.