This is the class where optimizatoin models are defined.
This provides t he ablility to acknoledge the creation of any slack variables that may have been created for solving this optimization problem.
This is the criteria that must be met in order to consider an optimization method converged. This may be input as a string, or as a number.
local
global
This property is used to distinguis between local and global optimization problems
some measure or estimate of uncertainty in the output parameter
This is the necessary accuracy required before terminating the application.
This is the objective function of the optimiation problem to be entered as a string. Actual evaluation of this function may be done through application of SWRL rules.
This is the maximum number of failed runs allowed before terminating the application.
This is used to define wheter there is a sigle or multiple objectives when solving this optimzation problem.
single
multiple
This is the maximum number of iterations allowed before terminating the application.
This is the ideal value, or target value, which this paramter would like to be.
This is the relative step size of the opitmization problem when using this method.
This is the necessary step size before terminating the application.
This is the penalty base associated with this optimization problem
maximize
minimize
This distinguishes whether the objective is to minimize of maximize the paremeters in order to reach the target value.
This si the penalty multiplier associated with this optimization problem
This is the penalty method assocaited with this optimization prbolem
This is the penalty value used for a failed run.