The GA Procedure
- Overview
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Getting Started
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SyntaxPROC GA StatementContinueFor CallCross CallDynamic_array CallEvaluateLC CallGetDimensions CallGetObjValues CallGetSolutions CallInitialize CallMarkPareto CallMutate CallObjective FunctionPackBits CallProgramming StatementsReadChild CallReadCompare CallReadMember CallReadParent CallReEvaluate CallSetBounds CallSetCompareRoutine CallSetCross CallSetCrossProb CallSetCrossRoutine CallSetElite CallSetEncoding CallSetFinalize CallSetMut CallSetMutProb CallSetMutRoutine CallSetObj CallSetObjFunc CallSetProperty CallSetSel CallSetUpdateRoutine CallShellSort CallShuffle CallUnpackBits FunctionUpdateSolutions CallWriteChild CallWriteMember Call
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DetailsUsing Multisegment EncodingUsing Standard Genetic Operators and Objective FunctionsDefining a User Fitness Comparison RoutineDefining User Genetic OperatorsDefining a User Update RoutineDefining an Objective FunctionDefining a User Initialization RoutineSpecifying the Selection StrategyIncorporating Heuristics and Local OptimizationsHandling ConstraintsOptimizing Multiple Objectives
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Examples
- References
The SetMutProb call sets the mutation probability. The input to the SetMutProb subroutine is as follows:
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p |
is the mutation probability. |
The SetMutProb subroutine is used to set the mutation probability for the genetic algorithm optimization. The probability p should be a number between 0 and 1, and is interpreted as the probability that a solution in the next generation should have the mutation operator applied to it. If a SetElite call has been made, then the elite solutions do not undergo mutation. Generally, a high mutation probability degrades the convergence of the genetic algorithm optimization, but some level of mutation is required to assure a thorough search and avoid premature convergence before the global optimum is found. Typical values for p are near 0.05 or less.