I have committed some changes, they allows handling of maximization problems
objFunc -> max
(subjected to some constraints)
via p.goal = 'max'
Currently LP, MILP, QP classes have no the possibility, it's only valid for NLP, NSP, GLP
of course, the parameter goal could be used in prob assignment or solve function as well:
p = NLP(..., goal='max')
r = p.solve(solverName, ... (other parameters), goal='max')
here's graphical output from modified nlp3.py (using -f instead of f, already in subversion).