This program generates the following problem

 minimize    1/2 xt G x + qt x 
 subject to  C x >=d
             A x =b


 where         2000  is the order of G and 
        1000  is the number of all the constraints
 n. of active constraints=          100
 n. of equalities=          500
 K(G)= 10**   4.00000000000000       rank(G)=         2000
  min. eigenvalue of G=   1.000000000000000E-004

      _   _ 
     |  A  |
 B = |     |
     |_ C _|

 K(B)= 10**   1.00000000000000      min. eigenvalue of B= 
  0.100000000000000     
 K(Zt G Z) = 10**   2.00000000000000       rank(Zt G Z)=         1400 
  min. eigenvalue of Zt G Z=   1.000000000000000E-002

 Uniform distribution for the eigenvalues of G
 Uniform distribution for the singular values of B

 Level of degeneracy=            1

 Sparsity of G =   99.8000000000000       Sparsity of B =
   99.8000000000000     

 The matrix G will be stored in: data.dat       
 The matrix B will be stored in: constr.dat     

 Non-zero elements of G=        8008

 maximum number of non-zero elements per row 
 of G (kg) =   13.0000000000000     

 Non-zero diagonal elements of G=        2000
 Obtained sparsity=   99.79980    

 n. of elements of  B =        4002
 n. trasf V=        1157
 non-zero diagonal elements of B=        1000
 Obtained sparsity=   99.79990    

 maximum number of non-zero elements per row 
 of B=   22.0000000000000