diet.m
% %解决经典饮食模型%营养指南，基于%美国农业部美国膳食指南，20狗万app足彩05 % http://www.health.gov/DietaryGuidelines/dga2005/ ncategories = 4;类别={“卡路里”;“蛋白质”;“脂肪”;“钠”};% minNutrition maxNutrition = [1800 2200;;%卡路里;%蛋白0 65;%脂肪0 1779];%钠n食品= 9; foods = {'hamburger'; 'chicken'; 'hot dog'; 'fries'; 'macaroni'; 'pizza'; 'salad'; 'milk'; 'ice cream'}; foodcost = [2.49; % hamburger 2.89; % chicken 1.50; % hot dog 1.89; % fries 2.09; % macaroni 1.99; % pizza 2.49; % salad 0.89; % milk 1.59]; % ice cream % calories protein fat sodium nutritionValues = [ 410 24 26 730; % hamburger 420 32 10 1190; % chicken 560 20 32 1800; % hot dog 380 4 19 270; % fries 320 12 10 930; % macaroni 320 15 12 820; % pizza 320 31 12 1230; % salad 100 8 2.5 125; % milk 330 8 10 180]; % ice cream nutritionValues = sparse(nutritionValues); model.modelName = 'diet'; % The variables are layed out as [ buy; nutrition] model.obj = [ foodcost; zeros(ncategories, 1)]; model.lb = [ zeros(nfoods, 1); categorynutrition(:, 1)]; model.ub = [ inf(nfoods, 1); categorynutrition(:, 2)]; model.A = [ nutritionValues' -speye(ncategories)]; model.rhs = zeros(ncategories, 1); model.sense = repmat('=', ncategories, 1); function printSolution(result) if strcmp(result.status, 'OPTIMAL') buy = result.x(1:nfoods); nutrition = result.x(nfoods+1:nfoods+ncategories); fprintf('\nCost: %f\n', result.objval); fprintf('\nBuy:\n') for f=1:nfoods if buy(f) > 0.0001 fprintf('%10s %g\n', foods{f}, buy(f)); end end fprintf('\nNutrition:\n') for c=1:ncategories fprintf('%10s %g\n', categories{c}, nutrition(c)); end else fprintf('No solution\n'); end end % Solve results = gurobi(model); printSolution(results); fprintf('\nAdding constraint at most 6 servings of dairy\n') milk = find(strcmp('milk', foods)); icecream = find(strcmp('ice cream', foods)); model.A(end+1,:) = sparse([1; 1], [milk; icecream], 1, ... 1, nfoods + ncategories); model.rhs(end+1) = 6; model.sense(end+1) = '<'; % Solve results = gurobi(model); printSolution(results) end
