Solution
A solution represents the evaluated inputs for on a problem definition.
Parameters
the inputs (name,value) pairs associated with the solution
the number of replications associated with the request that caused the creation of the solution. Since a solution can have multiple requests for evaluation, this will generally be different from the sample size (count) associated with the estimate.
the estimated objective function from the simulation oracle
the estimates of the responses associated with the response constraints
the iteration number of the solver request. That is, the number of times that the simulation oracle has been asked to evaluate (any) input.
Constructors
Properties
The estimated (average) value of the objective function
Allows comparison of solutions by the estimated objective function
The penalized objective function. That is, the estimated objective function plus the total penalty associated with violating the response constraints.
Allows comparison of solutions by the estimated objective function
The user may supply a penalty function to use when computing the response constraint violation penalty; otherwise the default penalty function is used.
The current value of the penalty function
The total penalty associated with violating the response constraints
The violation amount for each response constraint
The standard deviations of the estimated responses
Functions
Interprets the supplied map as inputs for the problem definition and returns true if the values are within functional constraints. False will be returned if at least one functional constraint is infeasible.
The supplied input is considered input feasible if it is feasible with respect to the defined input parameter ranges, the linear constraints, and the functional constraints.
Interprets the supplied map as inputs for the problem definition and returns true if the values are within the ranges defined for the variables. False will be returned if at least one input variable is not within its defined range.
Interprets the supplied map as inputs for the problem definition and returns true if the values are within linear constraints. False will be returned if at least one linear constraint is infeasible.
Tests if each response constraint is feasible. If all test feasible, then the solution is considered response feasible.
Computes a one-sided upper confidence interval for each response constraint to test if the interval contains zero. If the upper limit of the interval is less than 0.0, then we can be confident that response constraint is feasible. The individual confidence interval upper limits are based on a one-sided confidence interval on the mean response assuming normality. The upper limit is computed as (x_bar - b + t(level, n-1)*s/sqrt(n)) assuming a less-than constraint. The individual confidence interval levels are adjusted to meet the overall level of confidence.
Converts the solution to an instance of a ResponseMap
Converts the data in the solution to a list containing the data associated with the solution.