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: TriP.m
    path of file: ./repos/PlatEMO/PlatEMO/Algorithms/Multi-objective optimization/TriP
    
    the code of the file until where you have to start completion: classdef TriP < ALGORITHM
% <multi
    
function main(Algorithm,Problem)

            %% Parameter setting
            [delta,nr] = Algorithm.ParameterSet(0.9,2);

            %% Generate the weight vectors
            [W,Problem.N] = UniformPoint(Problem.N,Problem.M);
            T = ceil(Problem.N/10);

            %% Detect the neighbours of each solution
            B = pdist2(W,W);
            [~,B] = sort(B,2);
            B = B(:,1:T);

            %% Generate random population
            Population  = Problem.Initialization();
            Z           = min(Population.objs,[],1);
            Population1 = Problem.Initialization();
            Population2 = Problem.Initialization();
            alpha_c     = 2./(1+exp(1).^(-Problem.FE*10/(3*Problem.maxFE)))-1;
            para        = ceil(Problem.maxFE/Problem.N)/2 - ceil(Problem.FE/(3*Problem.N));

            %% Evaluate the Population
            Tc               = 0.9 * ceil(Problem.maxFE/Problem.N);
            last_gen         = 20;
            change_threshold = 1e-1;
            search_stage     = 1; % 1 for push stage,otherwise,it is in pull stage.
            max_change       = 1;
            epsilon_k        = 0;
            epsilon_0        = 0;
            cp               = 2;
            alpha            = 0.95;
            tao              = 0.05;
            ideal_points     = zeros(ceil(Problem.maxFE/Problem.N),Problem.M);
            nadir_points     = zeros(ceil(Problem.maxFE/Problem.N),Problem.M);
            arch             = archive(Population,Problem.N);

            %% Optimization
            while Algorithm.NotTerminated(Population)
                gen        = ceil(Problem.FE/(2*Problem.N));
                pop_cons   = Population.cons;
                cv         = overall_cv(pop_cons);
                population = [Population.decs,Population.objs,cv];
                rf         = sum(cv <= 1e-6) / Problem.N;
                ideal_points(gen,:) = Z;
                nadir_points(gen,:) = max(population(:,Problem.D + 1 : Problem.D + Problem.M),[],1);

                % The maximumrate of change of ideal and nadir points rk is calculated.
                if gen >= last_gen
                    max_change = calc_maxchange(ideal_points,nadir_points,gen,last_gen);
                end