Box-constrained OptimizationLast updated: 01/01/2023
- Problem: name of the benchmark problem.
- f(x): objective function value at solution.
- eps(C): convergency tolerance.
- eps(F): feasibility tolerance.
- # Iter.: number of iterations used by the solver.
- # x: number of variables in the benchmark problem.
- # b: number of simple bound constraints in the benchmark problem.
- # LC: number of linear constraints in the benchmark problem.
- # NLC: number of non-linear constraints in the benchmark problem.
- # f(x)-O: number of function calls used by the solver to evaluate objective function.
- # g(x)-O: number of function calls used by the solver to evaluate the gradient of the objective function.
- # H(x)-O: number of function calls used by the solver to evaluate the Hessian of the objective function.
- # f(x)-C: number of function calls used by the solver to evaluate the nonlinear constraint function.
- # g(x)-C: number of function calls used by the solver to evaluate the gradient of the nonlinear constraint function.
- Time(ms.): time in milliseconds used by the solver to find the solution.
CUTE box-constrained general optimization benchmark problems.
- Method choice:
Linear search - Discrete Newton
- Max number of iterations:
1000
| Problem |
f(x) |
eps(C) |
eps(F) |
# Iter. |
# x |
# b |
# LC |
# NLC |
# f(x)-O |
# g(x)-O |
# H(x)-O |
# f(x)-C |
# g(x)-C |
Time(ms.) |
| ALLINIT |
1.671e+001 |
1.0e-007 |
0.0e+000 |
12 |
4 |
3 |
0 |
0 |
51 |
51 |
0 |
0 |
0 |
74.1 |
| CAMEL6 |
-1.032e+000 |
1.0e-007 |
0.0e+000 |
5 |
2 |
2 |
0 |
0 |
21 |
21 |
0 |
0 |
0 |
76.5 |
| DECONVU |
5.259e-011 |
1.0e-007 |
0.0e+000 |
87 |
63 |
12 |
0 |
0 |
4970 |
4970 |
0 |
0 |
0 |
724.5 |
| EG1 |
-1.133e+000 |
1.0e-007 |
0.0e+000 |
13 |
3 |
2 |
0 |
0 |
67 |
67 |
0 |
0 |
0 |
65.1 |
| HART6 |
-3.323e+000 |
1.0e-007 |
0.0e+000 |
7 |
6 |
6 |
0 |
0 |
66 |
66 |
0 |
0 |
0 |
63.3 |
| HIMMELP1 |
-6.205e+001 |
1.0e-007 |
0.0e+000 |
15 |
2 |
2 |
0 |
0 |
47 |
47 |
0 |
0 |
0 |
65.3 |
| HOLMES |
1.248e+003 |
1.0e-007 |
0.0e+000 |
17 |
180 |
180 |
0 |
0 |
1819 |
1819 |
0 |
0 |
0 |
2428.0 |
| HS38 |
3.309e-014 |
1.0e-007 |
0.0e+000 |
43 |
4 |
4 |
0 |
0 |
280 |
280 |
0 |
0 |
0 |
67.5 |
| HS4 |
2.667e+000 |
1.0e-007 |
0.0e+000 |
2 |
2 |
2 |
0 |
0 |
11 |
11 |
0 |
0 |
0 |
62.9 |
| HS45 |
1.000e+000 |
1.0e-007 |
0.0e+000 |
3 |
5 |
5 |
0 |
0 |
27 |
27 |
0 |
0 |
0 |
60.6 |
| HS5 |
-1.913e+000 |
1.0e-007 |
0.0e+000 |
11 |
2 |
2 |
0 |
0 |
37 |
37 |
0 |
0 |
0 |
75.2 |
| LOGROS |
6.931e-001 |
1.0e-007 |
0.0e+000 |
3 |
2 |
2 |
0 |
0 |
14 |
14 |
0 |
0 |
0 |
65.9 |
| MAXLIKA |
1.149e+003 |
1.0e-007 |
0.0e+000 |
20 |
8 |
8 |
0 |
0 |
160 |
160 |
0 |
0 |
0 |
130.1 |
| MDHOLE |
1.873e-020 |
1.0e-007 |
0.0e+000 |
40 |
2 |
1 |
0 |
0 |
194 |
194 |
0 |
0 |
0 |
69.1 |
CUTE box-constrained general optimization benchmark problems.
- Method choice:
Linear search - Newton
- Max number of iterations:
1000
| Problem |
f(x) |
eps(C) |
eps(F) |
# Iter. |
# x |
# b |
# LC |
# NLC |
# f(x)-O |
# g(x)-O |
# H(x)-O |
# f(x)-C |
# g(x)-C |
Time(ms.) |
| ALLINIT |
1.671e+001 |
1.0e-007 |
0.0e+000 |
12 |
4 |
3 |
0 |
0 |
21 |
21 |
10 |
0 |
0 |
317.0 |
| CAMEL6 |
-1.032e+000 |
1.0e-007 |
0.0e+000 |
5 |
2 |
2 |
0 |
0 |
11 |
11 |
5 |
0 |
0 |
273.4 |
| DECONVU |
8.946e-011 |
1.0e-007 |
0.0e+000 |
61 |
63 |
12 |
0 |
0 |
444 |
444 |
60 |
0 |
0 |
576.4 |
| EG1 |
-1.133e+000 |
1.0e-007 |
0.0e+000 |
17 |
3 |
2 |
0 |
0 |
53 |
53 |
14 |
0 |
0 |
66.9 |
| HART6 |
-3.323e+000 |
1.0e-007 |
0.0e+000 |
7 |
6 |
6 |
0 |
0 |
24 |
24 |
7 |
0 |
0 |
62.2 |
| HIMMELP1 |
-6.205e+001 |
1.0e-007 |
0.0e+000 |
15 |
2 |
2 |
0 |
0 |
23 |
23 |
12 |
0 |
0 |
64.0 |
| HOLMES |
1.248e+003 |
1.0e-007 |
0.0e+000 |
17 |
180 |
180 |
0 |
0 |
19 |
19 |
10 |
0 |
0 |
3785.0 |
| HS38 |
1.061e-011 |
1.0e-007 |
0.0e+000 |
41 |
4 |
4 |
0 |
0 |
100 |
100 |
41 |
0 |
0 |
86.9 |
| HS4 |
2.667e+000 |
1.0e-007 |
0.0e+000 |
2 |
2 |
2 |
0 |
0 |
5 |
5 |
3 |
0 |
0 |
69.7 |
| HS45 |
1.000e+000 |
1.0e-007 |
0.0e+000 |
3 |
5 |
5 |
0 |
0 |
7 |
7 |
4 |
0 |
0 |
71.8 |
| HS5 |
-1.913e+000 |
1.0e-007 |
0.0e+000 |
11 |
2 |
2 |
0 |
0 |
19 |
19 |
9 |
0 |
0 |
63.3 |
| LOGROS |
6.931e-001 |
1.0e-007 |
0.0e+000 |
3 |
2 |
2 |
0 |
0 |
10 |
10 |
2 |
0 |
0 |
66.7 |
| MAXLIKA |
1.136e+003 |
1.0e-007 |
0.0e+000 |
69 |
8 |
8 |
0 |
0 |
111 |
111 |
49 |
0 |
0 |
234.5 |
| MDHOLE |
0.000e+000 |
1.0e-007 |
0.0e+000 |
40 |
2 |
1 |
0 |
0 |
113 |
113 |
40 |
0 |
0 |
65.8 |
CUTE box-constrained general optimization benchmark problems.
- Method choice:
Linear search - Quasi Newton
- Max number of iterations:
1000
| Problem |
f(x) |
eps(C) |
eps(F) |
# Iter. |
# x |
# b |
# LC |
# NLC |
# f(x)-O |
# g(x)-O |
# H(x)-O |
# f(x)-C |
# g(x)-C |
Time(ms.) |
| ALLINIT |
1.671e+001 |
1.0e-007 |
0.0e+000 |
16 |
4 |
3 |
0 |
0 |
34 |
34 |
0 |
0 |
0 |
67.7 |
| CAMEL6 |
-1.032e+000 |
1.0e-007 |
0.0e+000 |
10 |
2 |
2 |
0 |
0 |
23 |
23 |
0 |
0 |
0 |
64.4 |
| DECONVU |
2.854e-008 |
1.0e-007 |
0.0e+000 |
70 |
63 |
12 |
0 |
0 |
194 |
194 |
0 |
0 |
0 |
165.7 |
| EG1 |
-1.133e+000 |
1.0e-007 |
0.0e+000 |
7 |
3 |
2 |
0 |
0 |
16 |
16 |
0 |
0 |
0 |
67.1 |
| HART6 |
-3.323e+000 |
1.0e-007 |
0.0e+000 |
13 |
6 |
6 |
0 |
0 |
43 |
43 |
0 |
0 |
0 |
62.9 |
| HIMMELP1 |
-6.205e+001 |
1.0e-007 |
0.0e+000 |
26 |
2 |
2 |
0 |
0 |
402 |
402 |
0 |
0 |
0 |
67.5 |
| HOLMES |
1.248e+003 |
1.0e-007 |
0.0e+000 |
20 |
180 |
180 |
0 |
0 |
30 |
30 |
0 |
0 |
0 |
44.9 |
| HS38 |
2.353e-009 |
1.0e-007 |
0.0e+000 |
68 |
4 |
4 |
0 |
0 |
153 |
153 |
0 |
0 |
0 |
65.4 |
| HS4 |
2.667e+000 |
1.0e-007 |
0.0e+000 |
2 |
2 |
2 |
0 |
0 |
5 |
5 |
0 |
0 |
0 |
63.9 |
| HS45 |
1.000e+000 |
1.0e-007 |
0.0e+000 |
13 |
5 |
5 |
0 |
0 |
534 |
534 |
0 |
0 |
0 |
69.0 |
| HS5 |
-1.913e+000 |
1.0e-007 |
0.0e+000 |
10 |
2 |
2 |
0 |
0 |
23 |
23 |
0 |
0 |
0 |
67.1 |
| LOGROS |
1.077e-009 |
1.0e-007 |
0.0e+000 |
99 |
2 |
2 |
0 |
0 |
227 |
227 |
0 |
0 |
0 |
67.0 |
| MAXLIKA |
1.149e+003 |
1.0e-007 |
0.0e+000 |
33 |
8 |
8 |
0 |
0 |
70 |
70 |
0 |
0 |
0 |
96.4 |
| MDHOLE |
1.058e-035 |
1.0e-007 |
0.0e+000 |
71 |
2 |
1 |
0 |
0 |
217 |
217 |
0 |
0 |
0 |
68.4 |