getNumberOfEvaluations

Get number of function evaluations performed

Since R2025a

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    Syntax

    evalcount = getNumberOfEvaluations(obj)

    Description

    evalcount = getNumberOfEvaluations(obj) returns the number of function evaluations performed during optimization.

    example

    Examples

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    Open Live Script

    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);

    Figure contains 2 axes objects. Axes object 1 with title Population Diversity Plot, xlabel Number of Iterations, ylabel Population Diversity contains an object of type line. Axes object 2 with title Convergence Trend Plot, xlabel Number of Iterations, ylabel Fitness contains an object of type line.

    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

    Figure contains an axes object. The axes object with title Convergence Trend Plot, xlabel Number of Iterations, ylabel Fitness contains an object of type line.

    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

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    Optimizer, specified as an OptimizerSADEA or OptimizerTRSADEA object. The function returns the number of function evaluation performed during optimization by the optimizer specified in obj.

    Example: OptimizerSADEA

    Output Arguments

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    Number of function evaluations, returned as a positive integer.

    Version History

    Introduced in R2025a

    See Also

    Objects