I didn't know that SAGE could handle MILP (awesome!), I'm just playing
around with it now and was wondering if there was a way to remove a
constrain from a particular problem or indeed modify it without reseting
the whole problem.

For example:

Say I wanted to solve the problem described in the online tutorial, I would
input:

sage: p = MixedIntegerLinearProgram(maximization=False) sage: w =
p.new_variable(integer=True) sage: p.add_constraint(w[0] + w[1] + w[2]
- 14*w[3] == 0) sage: p.add_constraint(w[1] + 2*w[2] - 8*w[3] == 0)
sage: p.add_constraint(2*w[2] - 3*w[3] == 0) sage:
p.add_constraint(w[0] - w[1] - w[2] >= 0)sage: p.add_constraint(w[3]
>= 1) sage: _ = [ p.set_min(w[i], None) for i in range(1,4) ] sage:
p.set_objective(w[3]) sage: p.show()


If I wanted to change the last constraint to be w[0]-w[1]-w[2]>=1 can I do
this without resetting the whole p?

(Sorry to hijack the original question).

Thanks,
Vince

On 16 March 2012 10:45, Nathann Cohen <nathann.co...@gmail.com> wrote:

> Sage has a class name 'Mixed integer linear programming' for modeling
>> MIPs and class for LP Solver backends like Co-in, CPLEX, GLPK and Gurobi.
>> At the moment I haven't know any sage class only for vehicle routing
>> problem.
>>
>
> Yep ! There's a short tutorial about its use there :
> http://steinertriples.fr/ncohen/tut/LP/
>
> And we also have a TSP function implemented :-)
>
>
> http://www.sagemath.org/doc/reference/sage/graphs/generic_graph.html#sage.graphs.generic_graph.GenericGraph.traveling_salesman_problem
>
> Nathann
>
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-- 
Dr Vincent Knight
Cardiff School of Mathematics
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Cardiff
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www.vincent-knight.com
@drvinceknight <http://twitter.com/#!/drvinceknight>
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