You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: cDPEA.m
    path of file: ./repos/PlatEMO/PlatEMO/Algorithms/Multi-objective optimization/c-DPEA
    
    the code of the file until where you have to start completion: classdef cDPEA < ALGORITHM
% <multi> <real/integer/label/binary/permutation> <constrained>
% Constrained dual-population evolutionary algorithm

%------------------------------- Reference --------------------------------
% M. Ming, A. Trivedi, R. Wang, and D. Srinivasan, A dual-population based
% evolutionary algorithm for constrained multi-objective optimization, IEEE
% Transactions o
    
function is written by Mengjun Ming

    methods
        function main(Algorithm,Problem)
            %% Generate random population
            Population1 = Problem.Initialization(); 
            Population2 = Population1; 
            alpha       = 2./(1+exp(1).^(-Problem.FE*10/Problem.maxFE))-1;
            para        = ceil(Problem.maxFE/Problem.N)/2 - ceil(Problem.FE/Problem.N);

            %% Optimization
            while Algorithm.NotTerminated(Population1)
                % Re-rank
                Population1 = Population1(randperm(Problem.N));
                Population2 = Population2(randperm(Problem.N));
                Lia   = ismember(Population2.objs,Population1.objs, 'rows');
                gamma = 1-sum(Lia)/Problem.N;            
                [Population1,FrontNo1] = EnvironmentalSelection(Population1,Problem.N,alpha);
                [Population2,FrontNo2] = EnvironmentalSelection_noCon(Population2,Problem.N,alpha,gamma,para);

                % Offspring Reproduction
                Population_all   = [Population1,Population2];
                RankSolution_all = [FrontNo1,FrontNo2];
                MatingPool = TournamentSelection(2,2*Problem.N,RankSolution_all);
                Offspring  = OperatorGAhalf(Problem,Population_all(MatingPool));

                % Environmental Selection
                alpha = 2./(1+exp(1).^(-Problem.FE*10/Problem.maxFE)) - 1; 
                para  = ceil(Problem.maxFE/Problem.N)/2 - ceil(Problem.FE/Problem.N);
                [Population1,~] = EnvironmentalSelection([Population1,Offspring],Problem.N,alpha);
                [Population2,~] = EnvironmentalSelection_noCon([Population2,Offspring],Problem.N,alpha,gamma,para);
            end