This example shows the value of using sparse arithmetic when
you have a sparse problem. The matrix has
where you choose
n to be a large value. A full
matrix of size
n can use
up all available memory, but a sparse matrix presents no problem.
The problem is to minimize
x'*H*x/2 + f'*x subject to
x(1) + x(2) + ... + x(n) = 0,
f = [-1;-2;-3;...;-n].
Create the parameter
n and the utility
T. The matrix
T is a
sparse circulant matrix that is simply a helper for creating the sparse
positive-definite quadratic matrix
n = 30000; % Adjust n to a large value T = spalloc(n,n,n); % make a sparse circulant matrix r = 1:n-1; for m = r T(m,m+1)=1; end T(n,1) = 1;
Create a sparse vector
v. Then create
H by shifted versions of
T creates shifts of
v(n) = 0; v(1) = 1; v(2) = 2; v(4) = 3; v = (sparse(v))'; % Make a banded type of matrix H = spalloc(n,n,7*n); r = 1:n; for m = r H = H + v*v'; v = T*v; end
Take a look at the structure of
Create the problem vector
f and linear
f = -r; % linear term A = ones(1,n); b = 0;
Solve the quadratic programming problem with the
options = optimoptions(@quadprog,'Algorithm','interior-point-convex'); [x,fval,exitflag,output,lambda] = ... quadprog(H,f,A,b,,,,,,options); Minimum found that satisfies the constraints. Optimization completed because the objective function is non-decreasing in feasible directions, to within the selected value of the function tolerance, and constraints are satisfied to within the selected value of the constraint tolerance.
View the solution value, output structure, and Lagrange multiplier:
fval,output,lambda fval = -3.1331e+10 output = message: 'Minimum found that satisfies the constraints. Optimization com...' algorithm: 'interior-point-convex' firstorderopt: 1.1665e-04 constrviolation: 7.7762e-09 iterations: 6 cgiterations:  lambda = ineqlin: 1.5000e+004 eqlin: [0x1 double] lower: [30000x1 double] upper: [30000x1 double]
Since there are no lower bounds or upper bounds, all the values
The inequality constraint is active, since
On many computers you cannot create a full
n = 30000. So you can run this problem only
using sparse matrices.
H2 = zeros(3e4);
Out of memory. Type HELP MEMORY for your options.