Goal Weight

If an optimization setup has a cost function made up of multiple goals, you can assign a different weight to each goal. The goal with the greater weight is given more importance during the cost calculation.

The error function value is a weighted sum of the sub-goal errors. Each sub-goal, at each frequency at which it is evaluated, gives rise to a (positive) error value that represents the discrepancy between the simulated response and the goal value limit. If the response satisfies the goal value limit, then the error value is 0. Otherwise, the error value depends on the differences between the simulated response and the respective goal limit. The error function may be defined as follows:

where

• G is the number of sub-goals.
• W_j is the weight factor associated with the j^th sub-goal.
• N_j is the number of frequencies for the j^th sub-goal.
• e_i is the error contribution from the j^th sub-goal at the i^th frequency.

The value of e_i is determined by the band characteristics, target value, and the simulated response value. The choices for band characteristics are <=, =, and >=.

Band Characteristics (Condition)	ei evaluation where si is the simulated response and gi is the desired limit.
<=
=
>=

If the total error value is within the acceptable cost, the optimization stops.