Exercise 4.12* (Degeneracy and uniqueness - I)

Consider a general linear programming problem and suppose that we have a nondegenerate basic feasible solution to the primal. Show that the complementary slackness conditions lead to a system of equations for the dual vector that has a unique solution.

Answers

Proof. Consider the general primal problem and its dual

minimize cx subject toAx b , maximize pb subject topA = c p 0.

Now suppose that we have obtained a nondegenerate basic feasible solution x of the primal problem. By complementary slackness (Theorem 4.5), we have

i = 1,,m : pi (aix b i) = 0 j = 1,,n : (cj pA j) xj = 0.

In the exercise, we also assume that xi0 for all i = 1,,n. The second condition thus becomes cj pAj, j = 1,,n. In other words, we want to deduce the dual vector from the system of linear equations

pA = c.
(1)

Let B be the set of all indices at which constraints ai become active at x and let N denote the rest. By Definition 2.9, the rows ai, i B must be linearly independent. By Definition 2.10, there are exactly n such indices. Thus, the matrix AB is an n × n invertible matrix (cf. Theorem 1.2). Using this notation, we can equivalently rewrite (1) as

[pBpN ] [AB AN ] = c.
(2)

By construction, we have aix = bi for i B, and we have aix > bi for i N. Notice that the latter implies pi = 0, i N, when combined with the first complementary slackness condition. Thus, (2) equivalently becomes:

[pB0 ] [AB AN ] = pBA B = c.
(3)

As already mentioned, AB is invertible, and the above system will therefore always result in a unique solution. Rearranging the indices back to the original positions in (1), we obtain the desired vector. □

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2022-03-20 21:47
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