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“Easy” Integer Programming Problems: Network Flow Problems
EMIS 8374: Network Flows “Easy” Integer Programming Problems: Network Flow Problems updated 4 April 2004
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Basic Feasible Solutions
Standard Form
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Basic Feasible Solutions
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Vector-Matrix Representation
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LP Formulation of Shortest Path Example
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Matrix Representation
Observation: The last row of the matrix is equal to –1 times the sum of the other rows. MCNF LPs always have one redundant row.
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Matrix Representation without the constraint for node 6
A BFS: B = {x12, x13, x24, x35, x56}
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Solving for the BFS Constraints after non-basic variables are removed:
Solution: x24 = 0, x12 = 0, x13 = 1, x35 = 1, x56 = 1
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Solving for the BFS with Matrix Algebra
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Kramer’s (a.k.a Cramer’s) Rule
Component j of x = A-1b is Take the matrix A and replace column j with the vector b.
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Total Unimodularity Examples:
A square, integer matrix is unimodular if its determinant is 1 or -1. An integer matrix A is called totally unimodular (TU) if every square, nonsingular submatrix of A is unimodular. From Cramer’s rule, it follows that if A is TU and b is an integer vector, then every BFS of the constraint system Ax = b is integer. Examples: The matrix AB from the shortest path example is TU. The matrix A from the shortest path example is TU. The constraint matrix for any MCNF LP is TU.
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TU Theorem An integer matrix A is TU if
All entries are -1, 0 or 1 At most two non-zero entries appear in any column The rows of A can be partitioned into two disjoint sets such that If a column has two entries of the same sign, their rows are in different sets. If a column has two entries of different signs, their rows are in the same set. The matrix A is TU if and only if is AT TU. The matrix A is TU if and only if [A, I] is TU. Where I is the identity matrix.
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MCNF LPs are TU Flow Balance: A is TU, so AT is TU. Capacity
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