Dakota Reference Manual
Version 6.12
Explore and Predict with Confidence

Specify weights for each objective function
Alias: multi_objective_weights
Argument(s): REALLIST
Default: equal weights
For multiobjective optimization problems (where the number of objective functions is greater than 1), then a weights
specification provides a simple weightedsum approach to combining multiple objectives into a single objective:
Length: The weights
must have length equal to objective_functions. Thus, when scalar and/or field responses are specified, the number of weights
must equal the number of scalars plus the number of fields, not the total elements in the fields.
Default Behavior If weights are not specified, then each response is given equal weighting:
where, in both of these cases, a "minimization" responsesobjectvefunctions_sense will retain a positive weighting for a minimizer and a "maximization" sense will apply a negative weighting.
Usage Tips:
Weights are applied as multipliers, scales as charateristic values / divisors.
When scaling is active, it is applied to objective functions prior to any weights
and multiobjective sum formation. See the equations in objective_functions.