Failed
robust.testing.t_legacy.TestLegacy.test_simple_wing (from robust.testing.t_legacy.TestLegacy-20190924154011)
Failing for the past 1 build
(Since Failed
)
Error Message
The model is infeasible
Stacktrace
Traceback (most recent call last): File "/jenkins/workspace/robust_PullRequest/mosek/robust/testing/t_legacy.py", line 42, in test_simple_wing nominal_number_of_constraints, directly_uncertain_vars_subs) File "/jenkins/workspace/robust_PullRequest/mosek/robust/simulations/simulate.py", line 172, in print_variable_gamma_results number_of_time_average_solves) File "/jenkins/workspace/robust_PullRequest/mosek/robust/simulations/simulate.py", line 89, in simulate_robust_model linearizationTolerance=linearization_tolerance) File "/jenkins/workspace/robust_PullRequest/mosek/robust/robust.py", line 230, in robustsolve self.setup(verbosity, **options) File "/jenkins/workspace/robust_PullRequest/mosek/robust/robust.py", line 202, in setup feasible=True) File "/jenkins/workspace/robust_PullRequest/mosek/robust/robust.py", line 416, in find_number_of_piece_wise_linearization raise Exception("The model is infeasible") Exception: The model is infeasible
Standard Output
SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.3e+03) than the previous one (3.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.3e+03) than the previous one (3.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.8e+03) than the previous one (3.8e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.9e+03) than the previous one (3.9e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.5e+03) than the previous one (3.2e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.6e+03) than the previous one (3.5e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3.6e+03) than the previous one (3.6e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.