optimizeWithPlots
Optimize custom evaluation function and plot population density and convergence
Since R2025a
Description
optimizes the custom evaluation function specified in the optimizer object
opt = optimizeWithPlots(obj,iterations)obj using the number of iterations in iterations and
plots the population density and convergence.
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
length_lb = 3; % Lower bound for length length_ub = 7; % Upper bound for length width_lb = 0.11; % Lower bound for width width_ub = 0.13; % Upper bound for width Bounds = [length_lb width_lb; length_ub width_ub];
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;
Validate the optimizer setup.
validateSetup(s)
ans = logical
1
Run the optimization for 100 iterations.
figure optimizeWithPlots(s,100);

View the best member data.
bestDesign = s.getBestMemberData
bestDesign =
bestMemberData with properties:
member: [4.8004 0.1100]
performances: -4.7895
fitness: -4.7895
bestIterationId: 72
bestDesignValues = bestDesign.member
bestDesignValues = 1×2
4.8004 0.1100
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: [75×2 double]
performances: [75×1 double]
fitness: [75×1 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 = 105
Plot the convergence trend.
s.showConvergenceTrend

This code defines the evaluation function used in this example.
function fitness = customEvaluationOnlyObjective(designVariables) % Create geometry ant = design(dipole,75e6); ant.Length = designVariables(1); ant.Width = designVariables(2); % Calculate directivity % Optimizer always minimizes the objective hence reverse the sign to maximize gain. objective = max(max(pattern(ant,75e6))); objective = -objective; % As there are no constraints, fitness equals objective. fitness = objective; end
Input Arguments
Optimizer, specified as an OptimizerSADEA or OptimizerTRSADEA object. The function optimizes the custom evaluation
function associated with the optimizer object specified in
obj.
Example: OptimizerSADEA
Number of iterations for optimization, specified as a positive integer.
Example: 100
Data Types: double
Output Arguments
Optimized custom evaluation function parameters, returned as an OptimizerSADEA or OptimizerTRSADEA object. Use the getBestMemberData function to access the optimization results.
Version History
Introduced in R2025a
See Also
Objects
Functions
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