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Solving minimum K‐cardinality cut problems in planar graphs
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AbstractThe present work tackles a recent problem in the class of cardinality constrained combinatorial optimization problems for the planar graph case: the minimum k‐cardinality cut problem. Given an undirected edge‐weighted connected graph the min k‐cardinality cut problem consists in finding a partition of the vertex set V in two sets V1, V2 such that the number of the edges between V1 and V2 is exactly k and the sum of the weights of these edges is minimal. Although for general graphs the problem is already strongly ????????‐hard, we have found a pseudopolynomial algorithm for the planar graph case. This algorithm is based on the fact that the min k‐cardinality cut problem in the original graph is equivalent to a bi‐weighted exact perfect matching problem in a suitable transformation of the geometric dual graph. Because the Lagrangian relaxation of cardinality constraint yields a max cut problem and max cut is polynomially solvable in planar graphs, we also develop a Lagrangian heuristic for the min k‐cardinality cut in planar graphs. We compare the performance of this heuristic with the performance of a more general heuristic based on a Semidefinite Programming relaxation and on the Goemans and Williamson's random hyperplane technique. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 48(4), 195–208 2006
Title: Solving minimum K‐cardinality cut problems in planar graphs
Description:
AbstractThe present work tackles a recent problem in the class of cardinality constrained combinatorial optimization problems for the planar graph case: the minimum k‐cardinality cut problem.
Given an undirected edge‐weighted connected graph the min k‐cardinality cut problem consists in finding a partition of the vertex set V in two sets V1, V2 such that the number of the edges between V1 and V2 is exactly k and the sum of the weights of these edges is minimal.
Although for general graphs the problem is already strongly ????????‐hard, we have found a pseudopolynomial algorithm for the planar graph case.
This algorithm is based on the fact that the min k‐cardinality cut problem in the original graph is equivalent to a bi‐weighted exact perfect matching problem in a suitable transformation of the geometric dual graph.
Because the Lagrangian relaxation of cardinality constraint yields a max cut problem and max cut is polynomially solvable in planar graphs, we also develop a Lagrangian heuristic for the min k‐cardinality cut in planar graphs.
We compare the performance of this heuristic with the performance of a more general heuristic based on a Semidefinite Programming relaxation and on the Goemans and Williamson's random hyperplane technique.
© 2006 Wiley Periodicals, Inc.
NETWORKS, Vol.
48(4), 195–208 2006.
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