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A series of homework problems related to linear programming (lp) and the maximum flow problem. The first problem asks to formulate the problem of finding the best fitting line through a set of data points as an lp and discusses the reason for solving the dual. The second problem involves maximizing a linear function subject to certain constraints using the simplex method. The third problem asks if a pivot can move the feasible point without changing the cost and if a vector can re-enter the basis on the next pivot. The fourth problem deals with the dual of the maximum flow problem and shows how to construct a cut of minimum capacity separating the source and target nodes using the optimal solution.
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Maximize 3x 1 + 2x 2 + 4x 3
subject to
x 1 + x 2 + 2x 3 ≤ 4
2 x 1 + 3x 3 ≤ 5 2 x 1 + x 2 + 3x 3 ≤ 7 x 1 , x 2 , x 3 ≥ 0
xij −
∑ j
xji = w if i = s ; 0, if i 6 = s, t; −w if i = t
xij ≤ uij
0 ≤ xij
(a) Show that its dual is equivalent to:
min
∑ (i,j)∈E
uij yij
subject to
zi − zj + yij ≥ 0 (i, j) ∈ E
zs = 0, zt = 1
yij ≥ 0
(b) (extra credit-hard) Given any (not necessarily integral) optimal solution y∗, z∗^ of value W ∗^ to this dual linear program, show how to construct from z∗^ a cut separating s from t of value W ∗. Hint: make a clever use of complementary slackness (c) Deduce the max-flow–min-cut theorem: the value of the maximum flow from s to t is equal to th evalue of the minimum cut separating s and t.