On 15/08/2015 18:28, Terry Reedy wrote:
On 8/15/2015 3:21 AM, dieter wrote:
Ping Liu <yanzhiping...@gmail.com> writes:
...
For small cases, Python works well. But if we consider longer time
period.
then it would fail due to the memory usage issues. We have tested
several
case studies to check the memory use for different time period,
including
1) 2 hours in one day, 2) 24 hours in one day, 3) 20 days with 24 hours
each day, as well as 4) 30 days with 24 hours each day. The first 3
cases
are feasible while the last case gives out the memory error.
When we are testing the forth case, the memory error comes out while
creating the inequality constraints. The problem size is 1) Aeq: 12 *
26,
Aineq: 30 * 26; 2) Aeq: 144*268, Aineq:316*268; 3) Aeq: 2880*5284,
Aineq:
6244*5284; 4) Aeq: 4320 * 7924, Aineq is unknown due to the memory
error.
The solver is CPLEX (academic). It turns out that the solver is taking a
lot of memory as you can see in the memory test report. for the first
three
cases, different memory usage is observed, and it grows up dramatically
with the increase of the time period. 1) solver memory usage: 25.6
MB, 2)
19.5 MB; 3) solver memory usage: 830.0742 MB.
Make sure that the solver is using numpy arrays.
I doubt that as CPLEX was first released in 1988.
A very quick bit of searching found this
http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.linprog.html
which I believe is the equivalent of the Aeq and Aineq mentioned above.
Possibly a better option as must surely be using numpy, but as usual
there's only one way to find out? :)
--
My fellow Pythonistas, ask not what our language can do for you, ask
what you can do for our language.
Mark Lawrence
--
https://mail.python.org/mailman/listinfo/python-list
