cross.asv

GA（Simple Genetic Algorithm）是一种强大的智能多变量优化算法

function Ret=Cross(PCross,LenChrom,Individuals,SizePop,Opts,Pop)
% In this function,it fulfils a crossover among Chromosomes
% PCross    input  : probability of crossover
% LenChrom  input  : Length of a Chromosome
% Chrom     input  : set of Ret Chromosomes
% SizePop   input  : size of population
% Opts      input  : tag for choosing method of crossover
% Pop       input  : current serial number of generation and maximum gemeration
% Ret       output : new set of Chromosome
switch Opts
    case 'simple'  % cross at single position
        for i=1:SizePop
            % select two children at random
            Pick=rand(1,2);
            Index=ceil(Pick.*SizePop);
            while prod(Pick)==0 | Index(1)==Index(2)
                 Pick=rand(1,2);
                 Index=ceil(Pick.*SizePop);
            end
            % probability of crossover
            Pick=rand;
            if Pick>PCross
               continue;
            end
            % random position of crossover
            Pick=rand;
            while Pick==0
                 Pick=rand;
            end
            Pos=ceil(Pick.*sum(LenChrom));
            Tail1=bitand(Individuals.Chrom(Index(1)),2.^Pos-1);
            Tail2=bitand(Individuals.Chrom(Index(2)),2.^Pos-1);
            Individuals.Chrom(Index(1))=Individuals.Chrom(Index(1))-Tail1+Tail2;
            Individuals.Chrom(Index(2))=Individuals.Chrom(Index(2))-Tail2+Tail1;
       end
       Ret=Individuals.Chrom;
   case 'uniform' % uniform cross
        for i=1:SizePop
            % select two children at random
            Pick=rand(1,2);
            while prod(Pick)==0
                 Pick=rand(1,2);
            end
            Index=ceil(Pick.*SizePop);
            % random position of crossover
            Pick=rand;
            while Pick==0
                 Pick=rand;
            end
            if Pick>PCross
               continue;
            end
            % random position of crossover
            Pick=rand;
            while Pick==0
                 Pick=rand;
            end
            Mask=2^ceil(Pick*sum(LenChrom));
            Chrom1=Individuals.Chrom(Index(1));
            Chrom2=Individuals.Chrom(Index(2));
            for j=1:sum(LenChrom)
                v=bitget(Mask,j);  % from lower  to higher bit
                if v==1
                    Chrom1=bitset(Chrom1,...
                        j,bitget(Individuals.Chrom(Index(2)),j));
                    Chrom2=bitset(Chrom2,...
                        j,bitget(Individuals.Chrom(Index(1)),j));
                end
            end
            Individuals.Chrom(Index(1))=Chrom1;
            Individuals.Chrom(Index(2))=Chrom2;
        end
       Ret=Individuals.Chrom;
   case 'float'
       for i=1:SizePop
            % select two children at random
            Pick=rand(1,2);
            while prod(Pick)==0
                 Pick=rand(1,2);
            end
            Index=ceil(Pick.*SizePop);
            % random position of crossover
            Pick=rand;
            while Pick==0
                 Pick=rand;
            end
            if Pick>PCross
               continue;
            end
            % random position of crossover
            Pick=rand;
            while Pick==0
                 Pick=rand;
            end
            Pos=ceil(Pick.*sum(LenChrom));
            Pick=rand;
            V1=Individuals.Chrom(Index(1),Pos);
            V2=Individuals.Chrom(Index(2),Pos);
            Individuals.Chrom(Index(1),Pos)=Pick*V2+(1-Pick)*V1;
            Individuals.Chrom(Index(2),Pos)=Pick*V1+(1-Pick)*V2;
        end
        Ret=Individuals.Chrom;
end