sga and cmaes are made stochastic!!!! homebrew option deleted from cmaes
Kursawe study fixed.
Pareto Fronts plot is now step!!!!
Start developing V 1.1.4
Update to keplerian_toolbox 1.1.2
Upgrade to Eigen 3.1.1
Problem mga_1dsm coded in C++ (it is the equivalent of PyKEP python version) but 10 time faster
keplerian_toolbox update to the development branch
New bound setter implemented in base as to avoid the problem of not being able to call set_lb and set_ub separately if new_lb > ub and so on ....

Default value changed to 100 for maximum fly-by radius
We add the possibility of accounting of the launch vinf in the objfun
of the mga_1dsm problem
Redefining the constructor for mga_1ds in python if PyKEP is detected
Inverted the pareto front visualization as to assume minimization (kwarg 'post' in pl.step)
Update in the pareto front plot and gallery image
Options added to ipopt: nlp_scaling_method, mu_init, obj_scaling_factor
exposed crowding dist to python + starting to debug its computation
Buxfixing NSGA-II crowding distance computation.
screen output kwarg added to mbh
small changes
Merge branch 'development' into development_marcus
Beginning clean-up after bugfixing