I've been trying to do calculations on polytopes, and the associated rational polyhedral cones, cone lattice, and so on. One of the computations I've been trying to implement computes a list of inequalities that must hold true in terms of symbolic variables within the polytope, and I would like to complete the complete solution set to these inequalities.
For some of the relatively simple polytopes, the list of inequalities is rather small, and I'm able to use solve([list of inequalities], [list of relevant variables]) to solve for the complete solution set, which takes a minute or two. As the complexity of the polytope ramps up, though, very large lists of inequalities are generated, and solve() takes an immense amount of time. Is there a faster way to compute the complete set of solutions to a system of linear inequalities than solve()? From what I can see of Mixed Integer Linear Programming, I'm not sure it computes the full solution set. I'm not sure how I would go about expressing these inequalities in terms of matrices, or if that's even a valid approach for a linear inequality of several variables. Is there a different way of solving linear inequalities, or alternatively, is my understanding of MILP incorrect? Thanks, Ryan Davis -- You received this message because you are subscribed to the Google Groups "sage-support" group. To post to this group, send email to sage-support@googlegroups.com. To unsubscribe from this group, send email to sage-support+unsubscr...@googlegroups.com. Visit this group at http://groups.google.com/group/sage-support?hl=en.
