蚁群算法在栅格地图上的最短距离 MATLAB.rar_matlab 栅格地图_栅格地图_栅格蚁群_栅格蚁群算法_栅格路径规划

function [ROUTES,PL,Tau]=ACASP(G,Tau,K,M,S,E,Alpha,Beta,Rho,Q) %% --------------------------------------------------------------- % ACASP.m % ACS for Path Planning %% --------------------------------------------------------------- % input parameters % G gragh, which is 01 matrix, 1 represents obstcles % Tau initial pheromone matrix % K iterative times % M ant number for once iteration % S Start Point % E Goal point % Alpha parameter indicates the importance of pheromone % Beta parameter indicates the importance of visibility % Rho pheromone evaporation rate % Q pheromone accumulation parameter % % output parameters % ROUTES the route that every ant in every iteration % passes % PL the length that every ant in every iteration % passes % Tau output updated pheromone %% -------------------- variableinitialization----------------------------- D=G2D(G); N=size(D,1);%N is the peoblem scale(pixel number) MM=size(G,1); a=1;% edge length of pixel Ex=a*(mod(E,MM)-0.5);% goal point coordinate if Ex==-0.5 Ex=MM-0.5; end Ey=a*(MM+0.5-ceil(E/MM));% Y coordinate of goal point Eta=zeros(1,N); %construct the initialization matrix for i=1:N ix=a*(mod(i,MM)-0.5); if ix==-0.5 ix=MM-0.5; end iy=a*(MM+0.5-ceil(i/MM)); if i~=E Eta(1,i)=1/((ix-Ex)^2+(iy-Ey)^2)^0.5; else Eta(1,i)=100; end end ROUTES=cell(K,M);% use cell construct to load the passing route of every ant for every iteration PL=zeros(K,M);% use matrix to load the passing length of every ant for every iteration %% -----------iteration time is k, ant number is M-------------------- for k=1:K disp(k); for m=1:M %% First step: status initialization W=S;%set current point as the starting point Path=S;%initialize the passing route PLkm=0;%initialize the passing length TABUkm=ones(1,N);%initialize the forbbiden table TABUkm(S)=0;% eliminate this point for it is the starting point DD=D;%initialize adjacency matrix %% Second Step£ºChoose the nodes that can step forward DW=DD(W,:); DW1=find(DW<inf); for j=1:length(DW1) if TABUkm(DW1(j))==0 DW(j)=inf; end end LJD=find(DW<inf);% set of points can be selected Len_LJD=length(LJD);%number of points can be selected %% Colony stop condition£ºthere is no food or go into a impass while W~=E&&Len_LJD>=1 %% Third Step£ºthe method to choose the next step PP=zeros(1,Len_LJD); for i=1:Len_LJD PP(i)=(Tau(W,LJD(i))^Alpha)*(Eta(LJD(i))^Beta); end PP=PP/(sum(PP));%construct probability distributing Pcum=cumsum(PP); Select=find(Pcum>=rand); to_visit=LJD(Select(1));%the next step node %% Fourth Step£ºstatus update and record Path=[Path,to_visit];%Paths accumulation PLkm=PLkm+DD(W,to_visit);%Path length accumulation W=to_visit;%move to the next point for kk=1:N if TABUkm(kk)==0 DD(W,kk)=inf; DD(kk,W)=inf; end end TABUkm(W)=0;%eliminate the travelled point in the forbidden table DW=DD(W,:); DW1=find(DW<inf); for j=1:length(DW1) if TABUkm(DW1(j))==0 DW(j)=inf; end end LJD=find(DW<inf);%set of optional points Len_LJD=length(LJD);%number of optional points end %% Fifth Step£ºrecord the pate and length that every ant for every %% iteration passes ROUTES{k,m}=Path; if Path(end)==E PL(k,m)=PLkm; else PL(k,m)=inf; end end %% Sixth Step: update pheromone Delta_Tau=zeros(N,N);%initialize updating ammount for m=1:M if PL(k,m)<inf ROUT=ROUTES{k,m}; TS=length(ROUT)-1; PL_km=PL(k,m); for s=1:TS x=ROUT(s); y=ROUT(s+1); Delta_Tau(x,y)=Delta_Tau(x,y)+Q/PL_km; Delta_Tau(y,x)=Delta_Tau(y,x)+Q/PL_km; end end end Tau=(1-Rho).*Tau+Delta_Tau;%pheromone evaporates some and accumulates some end %% ---------------------------PLOT-------------------------------- plotif=1;%control parameter, determine if plot or not if plotif==1 %plot convergence curve meanPL=zeros(1,K); minPL=zeros(1,K); for i=1:K PLK=PL(i,:); Nonzero=find(PLK<inf); PLKPLK=PLK(Nonzero); meanPL(i)=mean(PLKPLK); minPL(i)=min(PLKPLK); end figure(1) plot(minPL,'b-'); hold on plot(meanPL,'r-'); grid on title('Convergence Curve£¨Average Length and Minimum Length£©'); xlabel('Iteration Times'); ylabel('Path Length'); legend('minPL','meanPL') %Plot Passing Graph figure(2) axis([0,MM,0,MM]) for i=1:MM for j=1:MM if G(i,j)==1 x1=j-1;y1=MM-i; x2=j;y2=MM-i; x3=j;y3=MM-i+1; x4=j-1;y4=MM-i+1; fill([x1,x2,x3,x4],[y1,y2,y3,y4],[0.2,0.2,0.2]); hold on else x1=j-1;y1=MM-i; x2=j;y2=MM-i; x3=j;y3=MM-i+1; x4=j-1;y4=MM-i+1; fill([x1,x2,x3,x4],[y1,y2,y3,y4],[1,1,1]); hold on end end end hold on ROUT=ROUTES{K,M}; LENROUT=length(ROUT); Rx=ROUT; Ry=ROUT; for ii=1:LENROUT Rx(ii)=a*(mod(ROUT(ii),MM)-0.5); if Rx(ii)==-0.5 Rx(ii)=MM-0.5; end Ry(ii)=a*(MM+0.5-ceil(ROUT(ii)/MM)); end plot(Rx,Ry) end title('Shortest Path'); axis([0,MM,0,MM]); plotif2=1;%Plot route for every iteration if plotif2==1 figure(3) axis([0,MM,0,MM]) for i=1:MM for j=1:MM if G(i,j)==1 x1=j-1;y1=MM-i; x2=j;y2=MM-i; x3=j;y3=MM-i+1; x4=j-1;y4=MM-i+1; fill([x1,x2,x3,x4],[y1,y2,y3,y4],[0.2,0.2,0.2]); hold on else x1=j-1;y1=MM-i; x2=j;y2=MM-i; x3=j;y3=MM-i+1; x4=j-1;y4=MM-i+1; fill([x1,x2,x3,x4],[y1,y2,y3,y4],[1,1,1]); hold on end end end for k=1:K PLK=PL(k,:); minPLK=min(PLK); pos=find(PLK==minPLK); m=pos(1); ROUT=ROUTES{k,m}; LENROUT=length(ROUT); Rx=ROUT; Ry=ROUT; for ii=1:LENROUT Rx(ii)=a*(mod(ROUT(ii),MM)-0.5); if Rx(ii)==-0.5 Rx(ii)=MM-0.5; end Ry(ii)=a*(MM+0.5-ceil(ROUT(ii)/MM)); end plot(Rx,Ry) hold on end end axis([0,MM,0,MM]) title('Routes that All the Ants Passed'); disp('Shortest Length is') disp(minPLK);