I would suggest taking a look at the python package networkx. It is a
wonderfully created path optimization and presentation package which
has a fair amount of extensabilty.
Basic lowest cost path solutions should be able to solve your
algorithmic needs here in polynomial time (Typically N**P time
I have a set of N blocks of different lengths. The length of each
block is a multiple of a basic unit. The blocks, once lined up, make a
path of distance equal to R. Let's say we have 5 blocks with the
following lengths: N_set_lengths = (1, 3, 2, 1, 3), then the path we
cover by lining them up is e
thanks, I was actually looking for a package only in python to do this
which can solve it directly. Since my problem is a nonlinear convex
optimization problem, there are a number of algorithms to get it
solved.
I will try using CVXOPT package.
Beliavsky wrote:
> Stefan Behnel wrote:
> &g
Stefan Behnel wrote:
> [EMAIL PROTECTED] wrote:
> > I need to do a quadratic optimization problem in python where the
> > constraints are quadratic and objective function is linear.
> >
> > What are the possible choices to do this.
>
> Too bad these homework as
[EMAIL PROTECTED] wrote:
> I need to do a quadratic optimization problem in python where the
> constraints are quadratic and objective function is linear.
>
> What are the possible choices to do this.
Too bad these homework assignments get trickier every time, isn't it?
