******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
 Ipopt is released as open source code under the Common Public License (CPL).
         For more information visit http://projects.coin-or.org/Ipopt
******************************************************************************

NOTE: You are using Ipopt by default with the MUMPS linear solver.
      Other linear solvers might be more efficient (see Ipopt documentation).


This is Ipopt version 3.9.1, running with linear solver mumps.

Number of nonzeros in equality constraint Jacobian...:        0
Number of nonzeros in inequality constraint Jacobian.:        1
Number of nonzeros in Lagrangian Hessian.............:        1

Total number of variables............................:        1
                     variables with only lower bounds:        0
                variables with lower and upper bounds:        1
                     variables with only upper bounds:        0
Total number of equality constraints.................:        0
Total number of inequality constraints...............:        1
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        1
        inequality constraints with only upper bounds:        0

iter    objective    	inf_pr   	inf_du 		lg(mu)  ||d||  		lg(rg) 	alpha_du 	alpha_pr  	ls
   0 	1.5000000e+000 	0.00e+000 	0.00e+000   	0.0 	0.00e+000    	-  	0.00e+000 	0.00e+000   	0
   1 	1.5000000e+000 	0.00e+000 	3.98e-012   	0.0 	4.00e-012    	-  	9.90e-001 	1.00e+000f  	1
   2 	1.4999999e+000 	0.00e+000 	3.20e-008   	3.9 	3.20e-008    	-  	1.00e+000 	1.00e+000f  	1
   3 	1.4999999e+000 	0.00e+000 	6.40e-009   	3.2 	6.40e-009    	-  	1.00e+000 	1.00e+000f  	1
   4 	1.4999999e+000 	0.00e+000 	1.28e-009   	2.5 	1.28e-009    	-  	1.00e+000 	1.00e+000f  	1
   5 	1.4999999e+000 	0.00e+000 	2.56e-010   	1.8 	2.56e-010    	-  	1.00e+000 	1.00e+000f  	1
   6 	1.4999999e+000 	0.00e+000 	5.12e-011   	1.1 	5.12e-011    	-  	1.00e+000 	1.00e+000f  	1
   7 	1.4999999e+000 	0.00e+000 	1.02e-011   	0.4 	1.02e-011    	-  	1.00e+000 	1.00e+000f  	1
   8 	1.4999999e+000 	0.00e+000 	2.05e-012  	-0.3 	2.05e-012    	-  	1.00e+000 	1.00e+000f  	1
   9 	1.4999999e+000 	0.00e+000 	4.10e-013  	-1.0 	4.10e-013    	-  	1.00e+000 	1.00e+000f  	1
iter    objective    	inf_pr   	inf_du 		lg(mu)  ||d||  		lg(rg) 	alpha_du 	alpha_pr  	ls
  10 	1.4999999e+000 	0.00e+000 	8.19e-014  	-1.7 	8.19e-014    	-  	1.00e+000 	1.00e+000f  	1
  11 	1.4999999e+000 	0.00e+000 	1.17e-014  	-2.5 	1.17e-014    	-  	1.00e+000 	1.00e+000f  	1
  12 	1.4999999e+000 	0.00e+000 	1.72e-017  	-8.5 	1.17e-020    	-  	9.97e-001 	1.00e+000   	0
  13 	1.4999999e+000 	0.00e+000 	2.75e-017  	-5.2 	2.75e-017    	-  	1.00e+000 	1.00e+000T  	0
  14 	1.4999999e+000 	0.00e+000 	7.21e-020  	-7.7 	7.21e-020    	-  	1.00e+000 	1.00e+000T  	0

Number of Iterations....: 14

                                   (scaled)                 (unscaled)
Objective...............:  1.4999999199920224e+000   1.4999999199920224e+000
Dual infeasibility......:  7.2057593396440895e-020   7.2057593396440895e-020
Constraint violation....:  0.0000000000000000e+000   0.0000000000000000e+000
Complementarity.........:  1.8014399328157875e-008   1.8014399328157875e-008
Overall NLP error.......:  1.8014399328157875e-008   1.8014399328157875e-008


Number of objective function evaluations             = 15
Number of objective gradient evaluations             = 15
Number of equality constraint evaluations            = 0
Number of inequality constraint evaluations          = 15
Number of equality constraint Jacobian evaluations   = 0
Number of inequality constraint Jacobian evaluations = 15
Number of Lagrangian Hessian evaluations             = 14
Total CPU secs in IPOPT (w/o function evaluations)   =      0.046
Total CPU secs in NLP function evaluations           =      0.000

EXIT: Optimal Solution Found.