Dot indexing is not supported for variables of this type.

Kindly help to resolve the error!! Thank You!!

classdef NSGA2Fed < handle
    properties
        nsga2 % modified this line
        options
        numObjectives
        numDecisionVars
        privacyConcerns
        communicationOverhead
        dataHeterogeneity
        maxGenerations
        paretoFront
        paretoFrontMetrics
    end
    
    methods
        function obj = NSGA2(varargin)
            if nargin > 0
                obj.options = varargin{1};
            else
                obj.options = struct();
            end
        end
        
        function obj = NSGA2Fed(numObjectives, numDecisionVars, nsga2, privacyConcerns, communicationOverhead, dataHeterogeneity, varargin)
            obj.numObjectives = numObjectives;
            obj.numDecisionVars = numDecisionVars;
            obj.nsga2 = nsga2; % modified this line
            obj.privacyConcerns = privacyConcerns;
            obj.communicationOverhead = communicationOverhead;
            obj.dataHeterogeneity = dataHeterogeneity;
            obj.maxGenerations = 50;
            obj.paretoFront = [];
            obj.paretoFrontMetrics = [];
            
            if nargin > 6
                for i = 1:2:length(varargin)
                    if strcmpi(varargin{i},'maxGenerations')
                        obj.maxGenerations = varargin{i+1};
                    end
                end
            end
            
            obj.nsga2.options; 
            obj.options.PopulationSize = 100;
            obj.options.MaxGenerations = obj.maxGenerations;
            obj.options.ParetoFraction = 1.0;
            obj.options.FunctionTolerance = 0.0001;
            obj.options.OutputFcn = @nsga2_outputfcn;
            
            function stop = nsga2_outputfcn(~, state, ~)
                stop = false;
                if strcmp(state,'done')
                    obj.paretoFront = obj.nsga2('paretofront');
                    obj.paretoFrontMetrics = obj.nsga2('paretoset');
                end
            end
        end
        
        function run(obj)
            obj.nsga2('solve',[],[],obj.options);
        end
        
        function optimize(obj, decisionVariables, constraints, objectives)
            % Calculate the number of clients
            numClients = round(1 + obj.dataHeterogeneity * randn(1));
            if numClients < 1
                numClients = 1;
            end
            
            % Divide decision variables and constraints among the clients
            clientDecisionVariables = cell(1, numClients);
            clientConstraints = cell(1, numClients);
            for i = 1:numClients
                % Determine the size of the decision variables and constraints
                clientSize = ceil(numel(decisionVariables) / numClients);
                
                % Divide the decision variables and constraints among the clients
                startIdx = (i - 1) * clientSize + 1;
                endIdx = min(i * clientSize, numel(decisionVariables));
                clientDecisionVariables{i} = decisionVariables(startIdx:endIdx);
                clientConstraints{i} = @(x) constraints([x(1:(end-2)/2), x(end/2+1:end-2), x(end-1:end)]);
            end
            
            % Define the multi-objective optimization problem for each client
            clientObjectives = cell(1, numClients);
            for i = 1:numClients
                clientObjectives{i} = @(x) objectives([x(1:(end-2)/2), x(end/2+1:end-2), x(end-1:end)]);
            end
            % Run the optimization algorithm for each client
            for i = 1:numClients
                fprintf('nsga2: %s\n', class(obj.nsga2));
                obj.nsga2.solve(clientDecisionVariables{i}, clientConstraints{i}, clientObjectives{i});
            end
            
            % Combine the Pareto fronts of all clients
            combinedParetoFront = obj.nsga2.ParetoFront;
            combinedParetoFrontFitness = obj.nsga2.ParetoFrontFitness;
            for i = 1:numClients
                combinedParetoFront = [combinedParetoFront; obj.nsga2.Population{i}.ParetoFront];
                combinedParetoFrontFitness = [combinedParetoFrontFitness; obj.nsga2.Population{i}.ParetoFrontFitness];
            end
            
            % Sort the combined Pareto front by fitness
            [~, idx] = sortrows(combinedParetoFrontFitness);
            obj.ParetoFront = combinedParetoFront(idx, :);
            obj.ParetoFrontFitness = combinedParetoFrontFitness(idx, :);
            
            % Apply privacy-preserving mechanisms if needed
            if obj.privacyConcerns
                obj.applyPrivacyPreservingMechanisms();
            end
            
            % Apply communication overhead
            obj.applyCommunicationOverhead();
            
            % Apply data heterogeneity
            obj.applyDataHeterogeneity();
        end
        
        %         function applyPrivacyPreservingMechanisms(obj)
        %             % Apply privacy-preserving mechanisms to the Pareto front
        %             % (e.g., differential privacy, securemulti-party computation, etc.)
        % %
        % % This is a placeholder function and can be implemented in
        % % subclasses of NSGA2Fed.
        % %
        % % Inputs:
        % % obj - the NSGA2Fed object
        %         % Apply the privacy-preserving mechanisms here
        %         % ...
        %     end
        
        function applyCommunicationOverhead(obj)
            % Apply communication overhead to the Pareto front
            %
            % Inputs:
            % obj - the NSGA2Fed object
            
            % Apply the communication overhead here
            obj.ParetoFront(:, obj.communicationObjectives) = ...
                obj.ParetoFront(:, obj.communicationObjectives) * (1 + obj.communicationOverhead);
        end
        
        function applyDataHeterogeneity(obj)
            % Apply data heterogeneity to the Pareto front
            %
            % Inputs:
            % obj - the NSGA2Fed object
            
            % Apply the data heterogeneity here
            obj.ParetoFront(:, obj.dataObjectives) = ...
                obj.ParetoFront(:, obj.dataObjectives) .* (1 + obj.dataHeterogeneity * randn(size(obj.ParetoFront(:, obj.dataObjectives))));
        end
    end 
end

test29

Generation 1: Number of Pareto fronts = 6

Generation 2: Number of Pareto fronts = 6

Generation 3: Number of Pareto fronts = 6

Generation 4: Number of Pareto fronts = 6

Generation 5: Number of Pareto fronts = 6

Generation 6: Number of Pareto fronts = 6

Generation 7: Number of Pareto fronts = 6

Generation 8: Number of Pareto fronts = 6

Generation 9: Number of Pareto fronts = 6

Generation 10: Number of Pareto fronts = 6

Dot indexing is not supported for variables of this type.

Error in NSGA2Fed (line 43)

obj.nsga2.options;

Error in test29 (line 21)

nsga2Fed = NSGA2Fed(numObjectives, numDecisionVars, nsga2, privacyConcerns, communicationOverhead, dataHeterogeneity,

'maxGenerations', 50);

Answer 1

[Gokul Nath S J]

Hi Sanjay,

Based on my understanding, it seems that you are facing an error at line number 43 of NSGA2Fed class. Since the test29 file is not available, I can only provide some workarounds which will be useful for debugging the code.

Place a breakpoint at line number 43 and print obj.nsga2 in the console. Make sure which all parameters are under it. It seems that obj.nsga2 is not a structure by itself. Kindly make sure the type of 'obj.nsga2' and call the required parameter in it accordingly.

with regards

Gokul Nath S J

[sanjay]

Thank You!!

Answer 2

[Walter Roberson]

classdef NSGA2Fed < handle
    ...
    methods
        function obj = NSGA2(varargin)

NSGA2 does not match the name of the class, NSGA2Fed, and NSGA2 is not marked as a static method. Therefore NSGA2 is not a class constructor: it is an ordinary method of NSGA2Fed. As such it needs to accept an object (of class NSGA2Fed) as a parameter.

        obj.nsga2 = nsga2; % modified this line

nsga2 here is some parameter that is being passed in to the NSGA2Fed constructor method, but we do not have any information about what its class is. In particular, as outside observers we have no reason to expect that it is a struct with a field named options or a class with a property or method named options . We just know that where the method NSGA2 assigned to obj.options, that that has nothing to do with whether there will be a options for whatever nsga2 is that is being passed in.

[sanjay]

Thank You!!