getInitializationData
Description
Examples
Create a dipole antenna resonating at 75 MHz and calculate its maximum directivity.
Choose its length and width as design variables. Provide lower and upper bounds of length and width.
referenceAnt = design(dipole,75e6); InitialDirectivity = max(max(pattern(referenceAnt,75e6)))
InitialDirectivity = 2.1002
Bounds = [3 0.11; 7 0.13];
Use the SADEA optimizer to optimize this dipole antenna for its directivity. Specify an evaluation function for optimization using the CustomEvaluationFunction
property of the OptimizerSADEA
object. The evaluation function used in this example is defined at the end of this example.
s = OptimizerSADEA(Bounds); s.CustomEvaluationFunction = @customEvaluationOnlyObjective;
Run the optimization for 100 iterations.
figure s.optimizeWithPlots(100);
View the best member data.
bestDesign = s.getBestMemberData
bestDesign = bestMemberData with properties: member: [4.7998 0.1101] performances: -4.7895 fitness: -4.7895 bestIterationId: 50
bestdesignValues = bestDesign.member
bestdesignValues = 1×2
4.7998 0.1101
Update the reference antenna with best design values from the optimizer. Calculate directivity of the optimized design.
Observe an increase in directivity value after optimization.
referenceAnt.Length = bestdesignValues(1); referenceAnt.Width = bestdesignValues(2); postOptimizationDirectivity = max(max(pattern(referenceAnt,75e6)))
postOptimizationDirectivity = 4.7895
View the surrogate model data used for prediction.
InitialData = s.getInitializationData
InitialData = initializationData with properties: members: [30×2 double] performances: [30×1 double] fitness: [30×1 double]
View the data for all iterations.
iterData = s.getIterationData
iterData = iterationData with properties: members: [68×2 double] performances: [68×1 double] fitness: [68×1 double]
Check if the algorithm has converged.
ConvergenceFlag = s.isConverged
ConvergenceFlag = logical
1
Check how many times the evaluation function is computed.
NumEvaluations = s.getNumberOfEvaluations
NumEvaluations = 98
Plot the convergence trend.
s.showConvergenceTrend
Following code defines the evaluation function used in this example.
function fitness = customEvaluationOnlyObjective(designVariables) fitness = []; try % Create geometry ant = design(dipole,75e6); ant.Length = designVariables(1); ant.Width = designVariables(2); catch % Handle errors during geometry creation. % High penalty value is used to handle errors. fitness = 1e6; end if isempty(fitness) try % Calculate directivity % Optimizer always minimizes the objective hence reverse the sign to maximize gain. objective = max(max(pattern(ant,75e6))); objective = -objective; catch % Handle errors during gain computation. % High penalty value is used to handle errors. objective = 1e6; end % As there are no constraints, fitness equals objective. fitness = objective; end end
Input Arguments
Optimizer, specified as an OptimizerSADEA
or OptimizerTRSADEA
object. The function returns data for members of the
optimizer object specified in obj
.
Example: OptimizerSADEA
Output Arguments
Optimizer member data at initialization, returned as an
initializationData
object with these properties:
members
– Initial design variable valuesperformances
– Vector of objective and constraints, with first element as objective and the rest as constraintsfitness
– Summation of objective and weighted constraint values at initialization
Version History
Introduced in R2025a
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