```% Section 8.2.1, Boyd & Vandenberghe "Convex Optimization"
% Joelle Skaf - 10/09/05
%
% Given two polyhedra C = {x | A1*x <= b1} and D = {x | A2*x <= b2}, the
% distance between them is the optimal value of the problem:
%           minimize    || x - y ||_2
%               s.t.    A1*x <= b1
%                       A2*y <= b2

% Input data
randn('state',0);
rand('state',0);

n  = 5;
m1 = 2*n;
m2 = 3*n;
A1 = randn(m1,n);
A2 = randn(m2,n);
b1 = rand(m1,1);
b2 = rand(m2,1) + A2*randn(n,1);

% Solution via CVX
cvx_begin
variables x(n) y(n)
minimize (norm(x - y))
A1*x <= b1;
A2*y <= b2;
cvx_end

% Displaying results
disp('------------------------------------------------------------------');
disp('The distance between the 2 polyhedra C and D is: ' );
disp(['dist(C,D) = ' num2str(cvx_optval)]);
```
```
Calling SDPT3 4.0: 31 variables, 11 equality constraints
For improved efficiency, SDPT3 is solving the dual problem.
------------------------------------------------------------

num. of constraints = 11
dim. of socp   var  =  6,   num. of socp blk  =  1
dim. of linear var  = 25
*******************************************************************
SDPT3: Infeasible path-following algorithms
*******************************************************************
version  predcorr  gam  expon  scale_data
NT      1      0.000   1        0
it pstep dstep pinfeas dinfeas  gap      prim-obj      dual-obj    cputime
-------------------------------------------------------------------
0|0.000|0.000|4.9e+01|7.0e+00|2.5e+03| 1.401402e+02  0.000000e+00| 0:0:00| chol  1  1
1|0.193|0.645|3.9e+01|2.5e+00|1.6e+03| 1.400766e+02 -3.014994e+01| 0:0:00| chol  1  1
2|0.911|0.702|3.5e+00|7.6e-01|5.8e+02| 1.795535e+02 -2.396806e+01| 0:0:00| chol  1  1
3|1.000|0.955|1.5e-05|3.5e-02|9.0e+01| 7.786451e+01 -4.168794e+00| 0:0:00| chol  1  1
4|0.885|1.000|3.5e-06|7.8e-05|1.2e+01| 9.239431e+00 -2.981045e+00| 0:0:00| chol  1  1
5|0.795|1.000|7.1e-07|8.2e-06|6.1e+00| 4.520886e+00 -1.536892e+00| 0:0:00| chol  1  1
6|1.000|0.871|1.2e-10|1.9e-06|1.9e+00| 7.328309e-01 -1.126315e+00| 0:0:00| chol  1  1
7|1.000|0.853|3.4e-10|3.4e-07|8.3e-01| 1.611200e-01 -6.710325e-01| 0:0:00| chol  1  1
8|0.850|0.859|5.0e-11|5.4e-08|1.6e-01|-3.730764e-01 -5.368661e-01| 0:0:00| chol  1  1
9|1.000|1.000|4.0e-11|7.6e-10|6.3e-02|-4.638722e-01 -5.269634e-01| 0:0:00| chol  1  1
10|0.918|0.986|3.2e-12|9.3e-11|4.7e-03|-5.044152e-01 -5.090797e-01| 0:0:00| chol  1  1
11|0.989|0.993|3.6e-14|9.1e-12|1.7e-04|-5.084285e-01 -5.086021e-01| 0:0:00| chol  1  1
12|0.981|0.987|1.5e-14|1.1e-12|3.0e-06|-5.085645e-01 -5.085675e-01| 0:0:00| chol  1  1
13|1.000|1.000|6.6e-12|1.0e-12|1.2e-07|-5.085670e-01 -5.085671e-01| 0:0:00| chol  1  1
14|1.000|1.000|1.5e-12|1.3e-12|1.7e-09|-5.085671e-01 -5.085671e-01| 0:0:00|
stop: max(relative gap, infeasibilities) < 1.49e-08
-------------------------------------------------------------------
number of iterations   = 14
primal objective value = -5.08567059e-01
dual   objective value = -5.08567060e-01
gap := trace(XZ)       = 1.72e-09
relative gap           = 8.55e-10
actual relative gap    = 8.53e-10
rel. primal infeas (scaled problem)   = 1.55e-12
rel. dual     "        "       "      = 1.32e-12
rel. primal infeas (unscaled problem) = 0.00e+00
rel. dual     "        "       "      = 0.00e+00
norm(X), norm(y), norm(Z) = 1.8e+00, 1.7e+00, 4.2e+00
norm(A), norm(b), norm(C) = 1.1e+01, 2.0e+00, 6.8e+00
Total CPU time (secs)  = 0.17
CPU time per iteration = 0.01
termination code       =  0
DIMACS: 1.5e-12  0.0e+00  2.3e-12  0.0e+00  8.5e-10  8.5e-10
-------------------------------------------------------------------

------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +0.508567

------------------------------------------------------------------
The distance between the 2 polyhedra C and D is:
dist(C,D) = 0.50857
```