function [Population,Score] = PopAnneal(options,GenomeLength,FitnessFcn, ...    state,thisScore,thisPopulation)R=10;L=GenomeLength*100;%T0=1000;alpha=0.8;%t = T0 * alpha^(state.Generation);nParents = size(thisPopulation,1);nAnneal = ceil(nParents / R /2);[Score,k] = sort(thisScore);Population  = thisPopulation(k,:);t = min(1/sqrt(eps),(Score(nAnneal*R)-Score(1))/log(2));%ta = 0.85;t = max(sqrt(eps),t);if isfield(options,'LinearConstr')    % Extract information about constraints    linCon = options.LinearConstr;    type = linCon.type;    % Sub-problem type is constrained?    if ~strcmpi(type,'unconstrained')        A = linCon.A;        LB = linCon.L;        UB = linCon.U;        Lbnd = LB((end-GenomeLength)+1:end);        Ubnd = UB((end-GenomeLength)+1:end);    else % Or unconstrained sub-problem        Lbnd = -(1e+20)*ones(GenomeLength,1);        Ubnd = (1e+20)*ones(GenomeLength,1);    endelse % Unconstrained 'main' problems;    type = 'unconstrained';    Lbnd = -(1e+20)*ones(GenomeLength,1);    Ubnd = (1e+20)*ones(GenomeLength,1);endLbnd2 = min(Population(1:nParents/2,:));%(1:nParents/2,:)Ubnd2 = max(Population(1:nParents/2,:));k2 = state.Generation;shrink = 0.95;stepSize = max(sqrt(eps),shrink^k2);Lbnd = (Lbnd2' + stepSize*Lbnd) / (1+stepSize);Ubnd = (Ubnd2' + stepSize*Ubnd) / (1+stepSize);Bound = [Lbnd';Ubnd'];ta = 0.78;ta = max(sqrt(eps),ta^(k2^(1/2)));shrink = 0.95;stepSize = max(sqrt(eps),shrink^k2);PopAnneal = [];ScoreAnneal = [];for i = 1:nAnneal    x = Population(i,:);    fx = Score(i);    [X2,fX2] = Anneal(x,fx,FitnessFcn,Bound,stepSize,A,LB,UB,R,L,t*ta);%    PopAnneal = [PopAnneal;X2];    ScoreAnneal = [ScoreAnneal;fX2];endx = mean(Population(1:nAnneal*R,:));%fx = feval(FitnessFcn,x);PopAnneal = [PopAnneal;x];ScoreAnneal = [ScoreAnneal;fx];[X2,fX2] = Anneal(x,fx,FitnessFcn,Bound,stepSize,A,LB,UB,R,L,t*ta);%PopAnneal = [PopAnneal;X2];ScoreAnneal = [ScoreAnneal;fX2];Population = [PopAnneal;Population];Score = [ScoreAnneal;Score];[Score,k] = sort(Score);Population  = Population(k,:);Population = Population(1:nParents,:);Score = Score(1:nParents,:);