mip1.m
% Copyright 2016, Gurobi Optimization, Inc.
% This example formulates and solves the following simple MIP model:
% maximize
% x + y + 2 z
% subject to
% x + 2 y + 3 z <= 4
% x + y >= 1
% x, y, z binary
names = {'x'; 'y'; 'z'};
try
clear model;
model.A = sparse([1 2 3; 1 1 0]);
model.obj = [1 1 2];
model.rhs = [4; 1];
model.sense = '<>';
model.vtype = 'B';
model.modelsense = 'max';
model.varnames = names;
gurobi_write(model, 'mip1.lp');
clear params;
params.outputflag = 0;
result = gurobi(model, params);
disp(result)
for v=1:length(names)
fprintf('%s %d\n', names{v}, result.x(v));
end
fprintf('Obj: %e\n', result.objval);
catch gurobiError
fprintf('Error reported\n');
end
