[SciPy-user] lagrange multipliers in python

fdu.xiaojf@gmai... fdu.xiaojf@gmai...
Sun Jun 17 10:07:42 CDT 2007

Hi Joachim,

Joachim Dahl wrote:
 > If your function is too complicated to evaluate derivatives,  chances
 > are that
 > it's not convex.  But you're still going to need the first and second
 > order derivatives
 > for Newton's method...
 > If you want to solve
 > min.  f(x)
 > s.t.    A*x = b
 > you could first find a feasible point x0 satisfying A*x0 = b (e.g., the
 > least-norm solution to A*x = b) and parametrize all feasible points as
 > z = x0+ B*y
 > where B spans the nullspace of A, i.e., A*B = 0.  Now you have an
 > unconstrained
 > problem
 > min.  f( x0 + B*y )
 > over the new variable y.

I still don't quite understand how to liminate linear equality
constraints.  Could you please point me to some web resources that
describe this method in detail? Or what key words I should use if I want
to google on the web?


Xiao Jianfeng

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