The GA Procedure
- Overview
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Getting Started
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Syntax
PROC GA Statement ContinueFor Call Cross Call Dynamicarray Call EvaluateLC Call GetDimensions Call GetObjValues Call GetSolutions Call Initialize Call MarkPareto Call Mutate Call Objective Function PackBits Call Programming Statements ReadChild Call ReadCompare Call ReadMember Call ReadParent Call ReEvaluate Call SetBounds Call SetCompareRoutine Call SetCross Call SetCrossProb Call SetCrossRoutine Call SetElite Call SetEncoding Call SetFinalize Call SetMut Call SetMutProb Call SetMutRoutine Call SetObj Call SetObjFunc Call SetProperty Call SetSel Call SetUpdateRoutine Call ShellSort Call Shuffle Call UnpackBits Function UpdateSolutions Call WriteChild Call WriteMember Call
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Details
Using Multisegment Encoding Using Standard Genetic Operators and Objective Functions Defining a User Fitness Comparison Routine Defining User Genetic Operators Defining a User Update Routine Defining an Objective Function Defining a User Initialization Routine Specifying the Selection Strategy Incorporating Heuristics and Local Optimizations Handling Constraints Optimizing Multiple Objectives
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Examples
- References
| ReEvaluate Call |
- call ReEvaluate ( <index> ) ;
The ReEvaluate call reruns the evaluation phase of the genetic algorithm. The inputs to the ReEvaluate subroutine are as follows:
index |
is a numeric scalar or array that specifies the indices of the solutions to be updated. The indices correspond to the order of the solutions obtained from a GetSolutions call. |
The ReEvaluate call recomputes the objective values for the current generation. You do not normally need to use this call, because the GA procedure evaluates the objective function during the optimization process in the evaluation phase. This subroutine should be called from a user update or finalize routine if a parameter that affects the objective value or solution is changed. The optional index parameter enables you to restrict the recomputation to the solution or subset of solutions specified. If the index parameter is not supplied, then the objective values of all the solutions will be recomputed.
For example, you might have a user objective function that can perform an additional local optimization if a particular parameter is set. If your update routine changes that parameter, then you should call the ReEvaluate subroutine to update the solutions and objective function values.