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Consider any linear programming model of $n$ variables and $m$ constraints which has multiple optimum solutions. If it is possible, I'd like to know the lower and upper limits (in terms of $n$, $m$ and possibly other elements as well) for the number of vertices from the feasible polyhedron that belongs to the set of optimum solutions.

I came to believe, that as long as the feasible polyhedron contains more than a single point, there would be at least 2 different vertices that belong to the set of optimum solutions. However, for the upper limit, I have no clue, except that the total number of vertices in a feasible polyhedron (which are not necessarily optimum) is at most $2^n$.

I'm not sure if my thoughts on this subject are correct, and maybe it's not possible to have a good estimation at all on this matter.

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Your belief that there will be two different vertices in the set of optimal solutions as long as the feasible polyhedron contains more than a single point is incorrect. In practice, most LPs have unique solutions. As far as an upper bound on the number of optimal vertices, let's assume that you have $m$ constraints including sign restrictions on the variables. For simplicity, let's also assume that $m>n$ (which need not be the case if you have sign-unrestricted variables). Since a vertex is the intersection of $n$ affinely independent constraint hyperplanes, in the worst case you would have $\binom{m}{n}$ vertices, all of which would be optimal if the objective function were constant. Under the given assumptions, that bound is valid, but I don't know that it is "good" if "good" means useful.

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  • $\begingroup$ What do you mean by "most LPs have unique solutions" ? $\endgroup$ – G Oliveira May 16 at 17:52
  • $\begingroup$ If I knew all vertices in the optimum solution of a given LP, from there, doesn't it make sense to try finding the hyperplane which intersects all opt solutions ? $\endgroup$ – G Oliveira May 16 at 17:57
  • $\begingroup$ Still regarding my last comment, I am interested in drafting optimum solution samples, which would be done by means of such hyperplane, as long as I am capable drafting only from the feasible region. $\endgroup$ – G Oliveira May 16 at 18:05
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    $\begingroup$ Isn't finding an optimal hyperplane trivial for any non-trivial objective? Just use "objective function = optimal value". $\endgroup$ – T_O May 16 at 18:35
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    $\begingroup$ @GOliveira In practice, problems with multiple optima are not uncommon, but problems with a single optimum are common and (I think) cover the majority of cases. Take a look at a sample of textbook problems and see how many have unique optima. $\endgroup$ – prubin May 17 at 18:05

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