多配送中心路径优化_QQ浏览器压缩包.zip

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多配送中心路径优化_QQ浏览器压缩包.zip 大约有40个文件

多配送中心路径优化/begin_s.m 972B
多配送中心路径优化/begin_s_v.m 769B
多配送中心路径优化/c101.mat 1.09KB
多配送中心路径优化/calObj.m 1.26KB
多配送中心路径优化/change.m 595B
多配送中心路径优化/cheapestIP.m 4.3KB
多配送中心路径优化/cls.m 1.39KB
多配送中心路径优化/costFuction.m 1.13KB
多配送中心路径优化/createfigure.m 948B
多配送中心路径优化/deal_Repeat.m 512B
多配送中心路径优化/deal_vehicles_customer.m 1.02KB
多配送中心路径优化/decode.m 2.86KB
多配送中心路径优化/draw_Best.m 1.69KB
多配送中心路径优化/farthestINS.m 1.32KB
多配送中心路径优化/Fitness.m 114B
多配送中心路径优化/GA_VRPTW.m 4.76KB
多配送中心路径优化/init.m 2.37KB
多配送中心路径优化/InitPopCW.m 453B
多配送中心路径优化/insert.m 965B
多配送中心路径优化/Judge.m 1.24KB
多配送中心路径优化/Judge_Del.m 399B
多配送中心路径优化/Judge_TW.m 1.39KB
多配送中心路径优化/leave_load.m 535B
多配送中心路径优化/linspecer.m 8.25KB
多配送中心路径优化/LocalSearch.m 1.42KB
多配送中心路径优化/Mutate.m 444B
多配送中心路径优化/OX.m 701B
多配送中心路径优化/part_length.m 325B
多配送中心路径优化/pszxxz.m 299B
多配送中心路径优化/Recombin.m 540B
多配送中心路径优化/Reins.m 335B
多配送中心路径优化/Relatedness.m 965B
多配送中心路径优化/Remove.m 2.04KB
多配送中心路径优化/Re_inserting.m 1.26KB
多配送中心路径优化/Select.m 268B
多配送中心路径优化/Sus.m 619B
多配送中心路径优化/travel_distance.m 694B
多配送中心路径优化/vehicle_load.m 912B
多配送中心路径优化/violateLoad.m 450B
多配送中心路径优化/violateTW.m 1009B

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多配送中心路径优化_QQ浏览器压缩包.zip

% function lineStyles = linspecer(N) % This function creates an Nx3 array of N [R B G] colors % These can be used to plot lots of lines with distinguishable and nice % looking colors. % % lineStyles = linspecer(N); makes N colors for you to use: lineStyles(ii,:) % % colormap(linspecer); set your colormap to have easily distinguishable % colors and a pleasing aesthetic % % lineStyles = linspecer(N,'qualitative'); forces the colors to all be distinguishable (up to 12) % lineStyles = linspecer(N,'sequential'); forces the colors to vary along a spectrum % % % Examples demonstrating the colors. % % LINE COLORS % N=6; % X = linspace(0,pi*3,1000); % Y = bsxfun(@(x,n)sin(x+2*n*pi/N), X.', 1:N); % C = linspecer(N); % axes('NextPlot','replacechildren', 'ColorOrder',C); % plot(X,Y,'linewidth',5) % ylim([-1.1 1.1]); % % SIMPLER LINE COLOR EXAMPLE % N = 6; X = linspace(0,pi*3,1000); % C = linspecer(N) % hold off; % for ii=1:N % Y = sin(X+2*ii*pi/N); % plot(X,Y,'color',C(ii,:),'linewidth',3); % hold on; % end % % COLORMAP EXAMPLE % A = rand(15); % figure; imagesc(A); % default colormap % figure; imagesc(A); colormap(linspecer); % linspecer colormap % % See also NDHIST, NHIST, PLOT, COLORMAP, 43700-cubehelix-colormaps %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % by Jonathan Lansey, March 2009-2013 � Lansey at gmail.com % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % %% credits and where the function came from % The colors are largely taken from: % http://colorbrewer2.org and Cynthia Brewer, Mark Harrower and The Pennsylvania State University % % % She studied this from a phsychometric perspective and crafted the colors % beautifully. % % I made choices from the many there to decide the nicest once for plotting % lines in Matlab. I also made a small change to one of the colors I % thought was a bit too bright. In addition some interpolation is going on % for the sequential line styles. % % %% function lineStyles=linspecer(N,varargin) if nargin==0 % return a colormap lineStyles = linspecer(128); return; end if ischar(N) lineStyles = linspecer(128,N); return; end if N<=0 % its empty, nothing else to do here lineStyles=[]; return; end % interperet varagin qualFlag = 0; colorblindFlag = 0; if ~isempty(varargin)>0 % you set a parameter? switch lower(varargin{1}) case {'qualitative','qua'} if N>12 % go home, you just can't get this. warning('qualitiative is not possible for greater than 12 items, please reconsider'); else if N>9 warning(['Default may be nicer for ' num2str(N) ' for clearer colors use: whitebg(''black''); ']); end end qualFlag = 1; case {'sequential','seq'} lineStyles = colorm(N); return; case {'white','whitefade'} lineStyles = whiteFade(N);return; case 'red' lineStyles = whiteFade(N,'red');return; case 'blue' lineStyles = whiteFade(N,'blue');return; case 'green' lineStyles = whiteFade(N,'green');return; case {'gray','grey'} lineStyles = whiteFade(N,'gray');return; case {'colorblind'} colorblindFlag = 1; otherwise warning(['parameter ''' varargin{1} ''' not recognized']); end end % *.95 % predefine some colormaps set3 = colorBrew2mat({[141, 211, 199];[ 255, 237, 111];[ 190, 186, 218];[ 251, 128, 114];[ 128, 177, 211];[ 253, 180, 98];[ 179, 222, 105];[ 188, 128, 189];[ 217, 217, 217];[ 204, 235, 197];[ 252, 205, 229];[ 255, 255, 179]}'); set1JL = brighten(colorBrew2mat({[228, 26, 28];[ 55, 126, 184]; [ 77, 175, 74];[ 255, 127, 0];[ 255, 237, 111]*.85;[ 166, 86, 40];[ 247, 129, 191];[ 153, 153, 153];[ 152, 78, 163]}')); set1 = brighten(colorBrew2mat({[ 55, 126, 184]*.85;[228, 26, 28];[ 77, 175, 74];[ 255, 127, 0];[ 152, 78, 163]}),.8); % colorblindSet = {[215,25,28];[253,174,97];[171,217,233];[44,123,182]}; colorblindSet = {[215,25,28];[253,174,97];[171,217,233]*.8;[44,123,182]*.8}; set3 = dim(set3,.93); if colorblindFlag switch N % sorry about this line folks. kind of legacy here because I used to % use individual 1x3 cells instead of nx3 arrays case 4 lineStyles = colorBrew2mat(colorblindSet); otherwise colorblindFlag = false; warning('sorry unsupported colorblind set for this number, using regular types'); end end if ~colorblindFlag switch N case 1 lineStyles = { [ 55, 126, 184]/255}; case {2, 3, 4, 5 } lineStyles = set1(1:N); case {6 , 7, 8, 9} lineStyles = set1JL(1:N)'; case {10, 11, 12} if qualFlag % force qualitative graphs lineStyles = set3(1:N)'; else % 10 is a good number to start with the sequential ones. lineStyles = cmap2linspecer(colorm(N)); end otherwise % any old case where I need a quick job done. lineStyles = cmap2linspecer(colorm(N)); end end lineStyles = cell2mat(lineStyles); end % extra functions function varIn = colorBrew2mat(varIn) for ii=1:length(varIn) % just divide by 255 varIn{ii}=varIn{ii}/255; end end function varIn = brighten(varIn,varargin) % increase the brightness if isempty(varargin), frac = .9; else frac = varargin{1}; end for ii=1:length(varIn) varIn{ii}=varIn{ii}*frac+(1-frac); end end function varIn = dim(varIn,f) for ii=1:length(varIn) varIn{ii} = f*varIn{ii}; end end function vOut = cmap2linspecer(vIn) % changes the format from a double array to a cell array with the right format vOut = cell(size(vIn,1),1); for ii=1:size(vIn,1) vOut{ii} = vIn(ii,:); end end %% % colorm returns a colormap which is really good for creating informative % heatmap style figures. % No particular color stands out and it doesn't do too badly for colorblind people either. % It works by interpolating the data from the % 'spectral' setting on http://colorbrewer2.org/ set to 11 colors % It is modified a little to make the brightest yellow a little less bright. function cmap = colorm(varargin) n = 100; if ~isempty(varargin) n = varargin{1}; end if n==1 cmap = [0.2005 0.5593 0.7380]; return; end if n==2 cmap = [0.2005 0.5593 0.7380; 0.9684 0.4799 0.2723]; return; end frac=.95; % Slight modification from colorbrewer here to make the yellows in the center just a bit darker cmapp = [158, 1, 66; 213, 62, 79; 244, 109, 67; 253, 174, 97; 254, 224, 139; 255*frac, 255*frac, 191*frac; 230, 245, 152; 171, 221, 164; 102, 194, 165; 50, 136, 189; 94, 79, 162]; x = linspace(1,n,size(cmapp,1)); xi = 1:n; cmap = zeros(n,3); for ii=1:3 cmap(:,ii) = pchip(x,cmapp(:,ii),xi); end cmap = flipud(cmap/255); end function cmap = whiteFade(varargin) n = 100; if nargin>0 n = varargin{1}; end thisColor = 'blue'; if nargin>1 thisColor = varargin{2}; end switch thisColor case {'gray','grey'} cmapp = [255,255,255;240,240,240;217,217,217;189,189,189;150,150,150;115,115,115;82,82,82;37,37,37;0,0,0]; case 'green' cmapp = [247,252,245;229,245,224;199,233,192;161,217,155;116,196,118;65,171,93;35,139,69;0,109,44;0,68,27]; case 'blue' cmapp = [247,251,255;222,235,247;198,219,239;158,202,225;107,174,214;66,146,198;33,113,181;8,81,156;8,48,107]; case 'red' cmapp = [255,245,240;254,224,210;252,187,161;252,146,114;251,106,74;239,59,44;203,24,29;165,15,21;103

多配送中心路径优化_QQ浏览器压缩包.zip

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