New version of ADNLPModels

[BaptisteCbl]

In order to use sparsity we need to update ADNLPModels.
Let's look at the new performance of ADNLPModels 0.6 :

• on goddard (all constraint) :
  • the problem

ocp = Model(variable=true)
Cd = 310
Tmax = 3.5
β = 500
b = 2
r0 = 1
v0 = 0
vmax = 0.1
m0 = 1
mf = 0.6
x0 = [ r0, v0, m0 ]
state!(ocp, 3)
control!(ocp, 1)
variable!(ocp, 1)
time!(ocp, 0, Index(1))
# use all possible types of constraints
# initial condition
constraint!(ocp, :initial, x0, :initial_constraint)
# final condition
constraint!(ocp, :final, Index(3), mf, :final_constraint)
# state constraint
constraint!(ocp, :state, (x,v)->x[2], -Inf, vmax, :state_con_v_ub)
# control constraint
constraint!(ocp, :control, (u,v)->u, -Inf, 1, :control_con_u_ub)
# mixed constraint
constraint!(ocp, :mixed, (x,u,v)->x[3], mf, Inf, :mixed_con_m_lb)
# variable constraint
constraint!(ocp, :variable, v->v, -Inf, 10, :variable_con_tf_ubx)
# state box
constraint!(ocp, :state, 1:2, [r0,v0], [r0+0.2, Inf], :state_box_rv)
#constraint!(ocp, :state, Index(2), v0, Inf, :state_box_vmin)
# control box
constraint!(ocp, :control, Index(1), 0, Inf, :control_box_lb)
# variable box
constraint!(ocp, :variable, Index(1), 0.01, Inf, :variable_box_tfmin)
objective!(ocp, :mayer,  (x0, xf, v) -> xf[1], :max)
function F0(x)
    r, v, m = x
    D = Cd * v^2 * exp(-β*(r - 1))
    return [ v, -D/m - 1/r^2, 0 ]
end
function F1(x)
    r, v, m = x
    return [ 0, Tmax/m, -b*Tmax ]
end
dynamics!(ocp, (x, u, v) -> F0(x) + u*F1(x) )
sol1 = solve(ocp, grid_size=100, print_level=5, tol=1e-8)

- the resolution
   - with ```ADNLPModels 0.5```

This is Ipopt version 3.14.12, running with linear solver MUMPS 5.5.1.

Number of nonzeros in equality constraint Jacobian...:     1904
Number of nonzeros in inequality constraint Jacobian.:      304
Number of nonzeros in Lagrangian Hessian.............:    82215

Total number of variables............................:      405
                     variables with only lower bounds:      203
                variables with lower and upper bounds:      101
                     variables with only upper bounds:        0
Total number of equality constraints.................:      304
Total number of inequality constraints...............:      304
        inequality constraints with only lower bounds:      101
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:      203

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   0 -1.0020000e+00 9.00e-01 1.00e+00   0.0 0.00e+00    -  0.00e+00 0.00e+00   0
   1 -1.0012479e+00 8.84e-01 3.36e+01  -0.7 2.16e+00    -  4.79e-02 1.78e-02h  1
   2 -1.0000125e+00 8.73e-01 1.53e+02   0.2 2.33e+01    -  9.09e-02 1.28e-02f  1
   3 -1.0002503e+00 8.66e-01 1.79e+05   0.9 3.97e+01    -  9.98e-01 7.63e-03h  1
   4 -1.0000025e+00 8.60e-01 1.94e+07   2.3 1.14e+01    -  7.90e-01 7.45e-03h  1
   5 -1.0000000e+00 8.58e-01 5.18e+08   2.3 1.12e+01    -  3.37e-02 1.27e-03h  1
   6 -9.9999999e-01 8.56e-01 3.30e+09   2.3 1.92e+01    -  1.62e-02 2.69e-03h  1
   7 -9.9999999e-01 8.56e-01 1.38e+10   2.3 4.25e+01    -  2.29e-03 6.17e-04h  1
   8 -9.9999999e-01 8.56e-01 5.20e+10   2.3 2.11e+02    -  2.38e-04 7.26e-05h  1
   9 -9.9999999e-01 8.56e-01 6.78e+07   2.3 2.40e+03    -  4.20e-06 2.55e-05h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  10r-9.9999999e-01 8.56e-01 1.00e+03  -0.1 0.00e+00    -  0.00e+00 2.85e-07R  4
  11r-1.0000008e+00 3.84e-01 1.06e+03  -0.4 2.21e+02    -  9.32e-01 2.13e-03f  1
  12 -1.0000000e+00 3.84e-01 7.81e+03  -1.2 5.87e+00    -  8.02e-02 6.23e-05f  1
  13 -9.9999999e-01 3.84e-01 1.29e+04  -6.7 2.26e+01    -  1.27e-04 7.40e-05h  1
  14 -9.9999999e-01 3.84e-01 1.05e+04  -1.6 4.06e+01    -  6.64e-05 7.54e-05h  1
  15 -9.9999999e-01 3.84e-01 4.24e+02  -2.1 7.75e+01    -  9.78e-05 1.27e-04h  1
  16 -9.9999999e-01 3.84e-01 3.44e+04  -6.7 8.67e+01    -  9.79e-05 2.00e-04h  1
  17 -9.9999999e-01 3.84e-01 8.72e+04  -6.7 7.28e+01    -  1.06e-04 2.47e-04h  1
  18 -9.9999999e-01 3.84e-01 2.61e+05   0.1 6.34e+01    -  7.64e-05 4.17e-04f  1
  19 -9.9999999e-01 3.84e-01 3.42e+05  -6.7 8.32e+01    -  8.48e-05 1.81e-04h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  20 -9.9999999e-01 3.84e-01 4.05e+05  -1.0 1.42e+02    -  7.78e-05 1.29e-04h  1
  21 -9.9999999e-01 3.84e-01 6.67e+05  -0.2 2.05e+02    -  8.43e-05 2.36e-04f  1
  22 -9.9999999e-01 3.83e-01 4.37e+05  -1.4 3.79e+02    -  1.21e-04 7.45e-05h  1
  23 -9.9999999e-01 3.83e-01 8.27e+05  -1.0 7.64e+02    -  1.51e-04 5.75e-05h  1
  24 -9.9999999e-01 3.83e-01 7.34e+06   1.2 3.97e+03    -  1.36e-04 2.16e-05f  1
  25 -9.9999999e-01 3.83e-01 1.81e+07   1.3 5.29e+03    -  6.64e-05 2.25e-05h  1
  26 -9.9999999e-01 3.83e-01 2.71e+08   1.3 4.87e+03    -  2.37e-04 1.37e-05h  1
  27r-9.9999999e-01 3.83e-01 1.00e+03   1.3 0.00e+00    -  0.00e+00 4.26e-07R  5
  28r-1.0001369e+00 5.40e-02 9.33e+02  -0.0 2.64e+00    -  6.94e-02 1.48e-01f  1
  29 -1.0000014e+00 5.18e-02 4.53e+01  -0.4 4.16e+00    -  2.45e-02 4.12e-02f  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  30 -1.0029688e+00 1.10e-02 1.11e+03  -0.6 4.68e-01    -  1.32e-01 9.57e-01h  1
  31 -1.0064489e+00 1.13e-02 8.19e+02  -0.7 3.47e+00    -  1.20e-01 1.94e-01f  1
  32 -1.0054017e+00 1.11e-03 1.30e+02  -1.0 2.29e-01    -  7.04e-01 9.90e-01f  1
  33 -1.0061209e+00 4.00e-05 8.68e+01  -1.4 1.69e-01    -  9.86e-01 9.92e-01f  1
  34 -1.0061145e+00 6.64e-07 1.55e-01  -3.0 9.70e-03    -  1.00e+00 1.00e+00h  1
  35 -1.0062260e+00 4.33e-07 1.27e-02  -4.4 1.14e-02    -  1.00e+00 1.00e+00h  1
  36 -1.0089915e+00 3.42e-04 3.06e+02  -4.8 6.33e-01    -  1.00e+00 8.34e-01h  1
  37 -1.0113475e+00 1.58e-04 4.64e-03  -5.1 4.04e-01    -  1.00e+00 1.00e+00h  1
  38 -1.0121499e+00 5.31e-05 1.28e+01  -5.5 8.70e-02    -  1.00e+00 9.70e-01h  1
  39 -1.0124152e+00 4.79e-05 5.34e-04  -5.9 1.42e-01    -  1.00e+00 1.00e+00h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  40 -1.0125142e+00 2.02e-05 1.73e+00  -6.4 1.38e-01    -  1.00e+00 9.76e-01h  1
  41 -1.0125597e+00 1.06e-05 6.64e-01  -7.1 1.15e-01    -  1.00e+00 9.81e-01h  1
  42 -1.0125686e+00 3.43e-06 6.43e-02  -7.7 8.29e-02    -  1.00e+00 9.91e-01h  1
  43 -1.0125704e+00 1.32e-06 1.57e-06  -8.0 1.64e-01    -  1.00e+00 1.00e+00h  1
  44 -1.0125714e+00 3.23e-07 1.03e-02  -8.8 6.56e-02    -  1.00e+00 9.87e-01h  1
  45 -1.0125716e+00 2.29e-09 1.03e-03  -9.7 8.61e-03    -  1.00e+00 9.92e-01h  1
  46 -1.0125716e+00 3.49e-10 2.95e-03 -11.0 9.89e-04    -  1.00e+00 8.47e-01h  1
  47 -1.0125716e+00 8.75e-11 1.39e-03 -11.0 1.65e-04    -  1.00e+00 7.49e-01h  1
  48 -1.0125716e+00 7.90e-14 1.31e-10 -11.0 4.15e-05    -  1.00e+00 1.00e+00h  1

Number of Iterations....: 48

                                   (scaled)                 (unscaled)
Objective...............:  -1.0125716186573468e+00   -1.0125716186573468e+00
Dual infeasibility......:   1.3143969887870330e-10    1.3143969887870330e-10
Constraint violation....:   4.2743586448068527e-14    7.8964612626464259e-14
Variable bound violation:   4.8296287126636192e-35    4.8296287126636192e-35
Complementarity.........:   1.3577979645348355e-11    1.3577979645348355e-11
Overall NLP error.......:   1.3577979645348355e-11    1.3143969887870330e-10


Number of objective function evaluations             = 58
Number of objective gradient evaluations             = 49
Number of equality constraint evaluations            = 58
Number of inequality constraint evaluations          = 58
Number of equality constraint Jacobian evaluations   = 51
Number of inequality constraint Jacobian evaluations = 51
Number of Lagrangian Hessian evaluations             = 48
Total seconds in IPOPT                               = 221.380

EXIT: Optimal Solution Found.

   - with ```ADNLPModels 0.6```

This is Ipopt version 3.14.12, running with linear solver MUMPS 5.5.1.

Number of nonzeros in equality constraint Jacobian...:     1904
Number of nonzeros in inequality constraint Jacobian.:      304
Number of nonzeros in Lagrangian Hessian.............:     1111

Total number of variables............................:      405
                     variables with only lower bounds:      203
                variables with lower and upper bounds:      101
                     variables with only upper bounds:        0
Total number of equality constraints.................:      304
Total number of inequality constraints...............:      304
        inequality constraints with only lower bounds:      101
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:      203

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   0 -1.0020000e+00 9.00e-01 1.00e+00   0.0 0.00e+00    -  0.00e+00 0.00e+00   0
   1 -1.0012479e+00 8.84e-01 3.36e+01  -0.7 2.16e+00    -  4.79e-02 1.78e-02h  1
   2 -1.0000125e+00 8.73e-01 1.53e+02   0.2 2.33e+01    -  9.09e-02 1.28e-02f  1
   3 -1.0002503e+00 8.66e-01 1.79e+05   0.9 3.97e+01    -  9.98e-01 7.63e-03h  1
   4 -1.0000025e+00 8.60e-01 1.94e+07   2.3 1.14e+01    -  7.90e-01 7.45e-03h  1
   5 -1.0000000e+00 8.58e-01 5.18e+08   2.3 1.12e+01    -  3.37e-02 1.27e-03h  1
   6 -9.9999999e-01 8.56e-01 3.30e+09   2.3 1.92e+01    -  1.62e-02 2.69e-03h  1
MUMPS returned INFO(1) = -9 and requires more memory, reallocating.  Attempt 1
  Increasing icntl[13] from 1000 to 2000.
   7 -9.9999999e-01 8.56e-01 1.38e+10   2.3 4.25e+01    -  2.29e-03 6.17e-04h  1
   8 -9.9999999e-01 8.56e-01 5.20e+10   2.3 2.11e+02    -  2.38e-04 7.26e-05h  1
   9 -9.9999999e-01 8.56e-01 6.78e+07   2.3 2.40e+03    -  4.20e-06 2.55e-05h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  10r-9.9999999e-01 8.56e-01 1.00e+03  -0.1 0.00e+00    -  0.00e+00 2.85e-07R  4
  11r-1.0000008e+00 3.84e-01 1.06e+03  -0.4 2.21e+02    -  9.32e-01 2.13e-03f  1
  12 -1.0000000e+00 3.84e-01 7.81e+03  -1.2 5.87e+00    -  8.02e-02 6.23e-05f  1
  13 -9.9999999e-01 3.84e-01 1.29e+04  -6.7 2.26e+01    -  1.27e-04 7.40e-05h  1
  14 -9.9999999e-01 3.84e-01 1.05e+04  -1.6 4.06e+01    -  6.64e-05 7.54e-05h  1
  15 -9.9999999e-01 3.84e-01 4.24e+02  -2.1 7.75e+01    -  9.78e-05 1.27e-04h  1
  16 -9.9999999e-01 3.84e-01 3.44e+04  -6.7 8.67e+01    -  9.79e-05 2.00e-04h  1
  17 -9.9999999e-01 3.84e-01 8.72e+04  -6.7 7.28e+01    -  1.06e-04 2.47e-04h  1
  18 -9.9999999e-01 3.84e-01 2.61e+05   0.1 6.34e+01    -  7.64e-05 4.17e-04f  1
  19 -9.9999999e-01 3.84e-01 3.42e+05  -6.7 8.32e+01    -  8.48e-05 1.81e-04h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  20 -9.9999999e-01 3.84e-01 4.05e+05  -1.0 1.42e+02    -  7.78e-05 1.29e-04h  1
  21 -9.9999999e-01 3.84e-01 6.67e+05  -0.2 2.05e+02    -  8.43e-05 2.36e-04f  1
  22 -9.9999999e-01 3.83e-01 4.37e+05  -1.4 3.79e+02    -  1.21e-04 7.45e-05h  1
  23 -9.9999999e-01 3.83e-01 8.27e+05  -1.0 7.64e+02    -  1.51e-04 5.75e-05h  1
  24 -9.9999999e-01 3.83e-01 7.34e+06   1.2 3.97e+03    -  1.36e-04 2.16e-05f  1
  25 -9.9999999e-01 3.83e-01 1.81e+07   1.3 5.29e+03    -  6.64e-05 2.25e-05h  1
  26 -9.9999999e-01 3.83e-01 2.71e+08   1.3 4.87e+03    -  2.37e-04 1.37e-05h  1
  27r-9.9999999e-01 3.83e-01 1.00e+03   1.3 0.00e+00    -  0.00e+00 4.26e-07R  5
  28r-1.0001369e+00 5.40e-02 9.33e+02  -0.0 2.64e+00    -  6.94e-02 1.48e-01f  1
  29 -1.0000014e+00 5.18e-02 4.53e+01  -0.4 4.16e+00    -  2.45e-02 4.12e-02f  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  30 -1.0029688e+00 1.10e-02 1.11e+03  -0.6 4.68e-01    -  1.32e-01 9.57e-01h  1
  31 -1.0064489e+00 1.13e-02 8.19e+02  -0.7 3.47e+00    -  1.20e-01 1.94e-01f  1
  32 -1.0054017e+00 1.11e-03 1.30e+02  -1.0 2.29e-01    -  7.04e-01 9.90e-01f  1
  33 -1.0061209e+00 4.00e-05 8.68e+01  -1.4 1.69e-01    -  9.86e-01 9.92e-01f  1
  34 -1.0061145e+00 6.64e-07 1.55e-01  -3.0 9.70e-03    -  1.00e+00 1.00e+00h  1
  35 -1.0062260e+00 4.33e-07 1.27e-02  -4.4 1.14e-02    -  1.00e+00 1.00e+00h  1
  36 -1.0089915e+00 3.42e-04 3.06e+02  -4.8 6.33e-01    -  1.00e+00 8.34e-01h  1
  37 -1.0113475e+00 1.58e-04 4.64e-03  -5.1 4.04e-01    -  1.00e+00 1.00e+00h  1
  38 -1.0121499e+00 5.31e-05 1.28e+01  -5.5 8.70e-02    -  1.00e+00 9.70e-01h  1
  39 -1.0124152e+00 4.79e-05 5.34e-04  -5.9 1.42e-01    -  1.00e+00 1.00e+00h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  40 -1.0125142e+00 2.02e-05 1.73e+00  -6.4 1.38e-01    -  1.00e+00 9.76e-01h  1
  41 -1.0125597e+00 1.06e-05 6.64e-01  -7.1 1.15e-01    -  1.00e+00 9.81e-01h  1
  42 -1.0125686e+00 3.43e-06 6.43e-02  -7.7 8.29e-02    -  1.00e+00 9.91e-01h  1
  43 -1.0125704e+00 1.32e-06 1.57e-06  -8.0 1.64e-01    -  1.00e+00 1.00e+00h  1
  44 -1.0125714e+00 3.23e-07 1.03e-02  -8.8 6.56e-02    -  1.00e+00 9.87e-01h  1
  45 -1.0125716e+00 2.29e-09 1.03e-03  -9.7 8.61e-03    -  1.00e+00 9.92e-01h  1
  46 -1.0125716e+00 3.49e-10 2.95e-03 -11.0 9.89e-04    -  1.00e+00 8.47e-01h  1
  47 -1.0125716e+00 8.75e-11 1.39e-03 -11.0 1.65e-04    -  1.00e+00 7.49e-01h  1
  48 -1.0125716e+00 7.90e-14 1.31e-10 -11.0 4.15e-05    -  1.00e+00 1.00e+00h  1

Number of Iterations....: 48

                                   (scaled)                 (unscaled)
Objective...............:  -1.0125716186573470e+00   -1.0125716186573470e+00
Dual infeasibility......:   1.3143941346770524e-10    1.3143941346770524e-10
Constraint violation....:   4.2854608750531042e-14    7.9047879353311146e-14
Variable bound violation:   3.6473273240036200e-36    3.6473273240036200e-36
Complementarity.........:   1.3577979558037065e-11    1.3577979558037065e-11
Overall NLP error.......:   1.3577979558037065e-11    1.3143941346770524e-10


Number of objective function evaluations             = 58
Number of objective gradient evaluations             = 49
Number of equality constraint evaluations            = 58
Number of inequality constraint evaluations          = 58
Number of equality constraint Jacobian evaluations   = 51
Number of inequality constraint Jacobian evaluations = 51
Number of Lagrangian Hessian evaluations             = 48
Total seconds in IPOPT                               = 908.516

EXIT: Optimal Solution Found.

• on double integrator (min tf) :
  • the problem

# min tf
ocp1 = Model(variable=true)
state!(ocp1, 2)
control!(ocp1, 1)
variable!(ocp1, 1)
time!(ocp1, 0, Index(1))
constraint!(ocp1, :initial, [0,0], :initial_constraint)
constraint!(ocp1, :final, [1,0], :final_constraint)
constraint!(ocp1, :control, -1, 1, :control_constraint)
constraint!(ocp1, :variable, 0.1, 10, :variable_constraint)
dynamics!(ocp1, (x, u, v) ->  [x[2], u])
objective!(ocp1, :mayer, (x0, xf, v) -> v)
sol1 = solve(ocp1, grid_size=100, print_level=5, tol=1e-12)

- the resolution
   - with ```ADNLPModels 0.5```

This is Ipopt version 3.14.12, running with linear solver MUMPS 5.5.1.

Number of nonzeros in equality constraint Jacobian...:     1004
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:    46360

Total number of variables............................:      304
                     variables with only lower bounds:        0
                variables with lower and upper bounds:      102
                     variables with only upper bounds:        0
Total number of equality constraints.................:      204
Total number of inequality constraints...............:        0
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:        0

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   0  1.0999999e-01 9.00e-01 6.03e-04   0.0 0.00e+00    -  0.00e+00 0.00e+00   0
   1  2.4500755e-01 8.88e-01 4.06e+01  -6.0 1.01e+01    -  9.91e-04 1.35e-02h  4
   2  7.5697512e-01 8.41e-01 7.57e+01   0.0 9.69e+00    -  2.08e-01 5.29e-02h  3
   3  3.1479409e+00 6.57e-03 7.71e+02   0.7 5.24e+00    -  1.00e+00 1.00e+00H  1
   4  2.8932152e+00 3.20e-04 1.39e+02  -0.6 2.55e-01   2.0 1.00e+00 1.00e+00h  1
   5  2.8598351e+00 1.82e-06 2.61e+00  -2.4 3.34e-02   1.5 1.00e+00 1.00e+00h  1
   6  2.8520124e+00 3.22e-07 8.16e-02  -3.9 7.82e-03   1.0 1.00e+00 1.00e+00h  1
   7  2.2964778e+00 3.95e-03 9.72e-02  -3.4 1.40e+00    -  1.00e+00 5.07e-01f  1
   8  2.1470689e+00 3.19e-03 8.80e-02  -9.5 3.31e+00    -  2.87e-01 1.94e-01h  1
   9  2.1009850e+00 2.87e-03 8.12e-02  -3.1 7.26e+00    -  1.00e+00 8.80e-02f  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  10  1.9907879e+00 1.52e-03 4.61e-02  -3.5 6.54e-01    -  9.98e-01 4.95e-01h  1
  11  2.0027147e+00 2.15e-04 5.50e-03  -4.0 6.82e-01    -  1.00e+00 8.54e-01h  1
  12  2.0017393e+00 3.19e-05 8.01e-04  -4.9 6.01e-01    -  1.00e+00 8.52e-01h  1
  13  2.0008059e+00 9.68e-07 2.81e-06  -5.2 2.20e-01    -  9.51e-01 1.00e+00h  1
  14  2.0002060e+00 1.03e-07 2.15e-07  -7.3 2.48e-02    -  9.96e-01 9.99e-01h  1
  15  2.0002000e+00 2.43e-11 2.35e-10 -12.3 7.31e-04    -  9.99e-01 1.00e+00h  1
  16  2.0002000e+00 1.11e-16 1.01e-15 -12.3 3.00e-07    -  1.00e+00 1.00e+00h  1

Number of Iterations....: 16

                                   (scaled)                 (unscaled)
Objective...............:   2.0002000200540007e+00    2.0002000200540007e+00
Dual infeasibility......:   1.0105428010020209e-15    1.0105428010020209e-15
Constraint violation....:   1.1102230246251565e-16    1.1102230246251565e-16
Variable bound violation:   9.9744974502158357e-09    9.9744974502158357e-09
Complementarity.........:   5.0002173720839694e-13    5.0002173720839694e-13
Overall NLP error.......:   5.0002173720839694e-13    5.0002173720839694e-13


Number of objective function evaluations             = 26
Number of objective gradient evaluations             = 17
Number of equality constraint evaluations            = 26
Number of inequality constraint evaluations          = 0
Number of equality constraint Jacobian evaluations   = 17
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations             = 16
Total seconds in IPOPT                               = 18.175

EXIT: Optimal Solution Found.

   - with ```ADNLPModels 0.6```

This is Ipopt version 3.14.12, running with linear solver MUMPS 5.5.1.

Number of nonzeros in equality constraint Jacobian...:     1004
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:      202

Total number of variables............................:      304
                     variables with only lower bounds:        0
                variables with lower and upper bounds:      102
                     variables with only upper bounds:        0
Total number of equality constraints.................:      204
Total number of inequality constraints...............:        0
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:        0

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   0  1.0999999e-01 9.00e-01 6.03e-04   0.0 0.00e+00    -  0.00e+00 0.00e+00   0
   1  2.4500755e-01 8.88e-01 4.06e+01  -6.0 1.01e+01    -  9.91e-04 1.35e-02h  4
   2  7.5697512e-01 8.41e-01 7.57e+01   0.0 9.69e+00    -  2.08e-01 5.29e-02h  3
   3  3.1479409e+00 6.57e-03 7.71e+02   0.7 5.24e+00    -  1.00e+00 1.00e+00H  1
   4  2.8932152e+00 3.20e-04 1.39e+02  -0.6 2.55e-01   2.0 1.00e+00 1.00e+00h  1
   5  2.8598351e+00 1.82e-06 2.61e+00  -2.4 3.34e-02   1.5 1.00e+00 1.00e+00h  1
   6  2.8520124e+00 3.22e-07 8.16e-02  -3.9 7.82e-03   1.0 1.00e+00 1.00e+00h  1
   7  2.2964778e+00 3.95e-03 9.72e-02  -3.4 1.40e+00    -  1.00e+00 5.07e-01f  1
   8  2.1470689e+00 3.19e-03 8.80e-02  -9.5 3.31e+00    -  2.87e-01 1.94e-01h  1
   9  2.1009850e+00 2.87e-03 8.12e-02  -3.1 7.26e+00    -  1.00e+00 8.80e-02f  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
  10  1.9907879e+00 1.52e-03 4.61e-02  -3.5 6.54e-01    -  9.98e-01 4.95e-01h  1
  11  2.0027147e+00 2.15e-04 5.50e-03  -4.0 6.82e-01    -  1.00e+00 8.54e-01h  1
  12  2.0017393e+00 3.19e-05 8.01e-04  -4.9 6.01e-01    -  1.00e+00 8.52e-01h  1
  13  2.0008059e+00 9.68e-07 2.81e-06  -5.2 2.20e-01    -  9.51e-01 1.00e+00h  1
  14  2.0002060e+00 1.03e-07 2.15e-07  -7.3 2.48e-02    -  9.96e-01 9.99e-01h  1
  15  2.0002000e+00 2.43e-11 2.35e-10 -12.3 7.31e-04    -  9.99e-01 1.00e+00h  1
  16  2.0002000e+00 1.11e-16 9.00e-16 -12.3 3.00e-07    -  1.00e+00 1.00e+00h  1

Number of Iterations....: 16

                                   (scaled)                 (unscaled)
Objective...............:   2.0002000200540007e+00    2.0002000200540007e+00
Dual infeasibility......:   8.9952049853950527e-16    8.9952049853950527e-16
Constraint violation....:   1.1102230246251565e-16    1.1102230246251565e-16
Variable bound violation:   9.9744974502158357e-09    9.9744974502158357e-09
Complementarity.........:   5.0002173720802142e-13    5.0002173720802142e-13
Overall NLP error.......:   5.0002173720802142e-13    5.0002173720802142e-13


Number of objective function evaluations             = 26
Number of objective gradient evaluations             = 17
Number of equality constraint evaluations            = 26
Number of inequality constraint evaluations          = 0
Number of equality constraint Jacobian evaluations   = 17
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations             = 16
Total seconds in IPOPT                               = 36.802

EXIT: Optimal Solution Found.

As we can see the number of non-zero is way lower with the new version however the computation time is higher, it is not expected.

p.s.: furthermore, with the new version of this package, there is an error in the problem :

CTDirect.jl/test/suite/double_integrator.jl

Line 60 in ae36b96

# max t0 (free t0 and tf)

It gives an error due to interpolation because Interpolations.jl require t0 < tf, so adding the constraint :

constraint!(ocp4, :variable, v -> v[2]-v[1], 0, Inf, :positiv_time)

make the problem solvable. Maybe ctgradient in CTBase must be modified to handle tf < t0.