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G. Vijayan, "Generalization of MinCut Partitioning to Tree Structures and its Applications," IEEE Transactions on Computers, vol. 40, no. 3, pp. 307314, March, 1991.  
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@article{ 10.1109/12.76407, author = {G. Vijayan}, title = {Generalization of MinCut Partitioning to Tree Structures and its Applications}, journal ={IEEE Transactions on Computers}, volume = {40}, number = {3}, issn = {00189340}, year = {1991}, pages = {307314}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.76407}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Computers TI  Generalization of MinCut Partitioning to Tree Structures and its Applications IS  3 SN  00189340 SP307 EP314 EPD  307314 A1  G. Vijayan, PY  1991 KW  minimisation; mincut partitioning; tree structures; nodes; hypergraph; vertices; cost function; routing; hyperedges; VLSI design applications; iterative improvement heuristic; pins; computational complexity; data structures; minimisation; trees (mathematics). VL  40 JA  IEEE Transactions on Computers ER   
A generalization of the mincut partitioning problem, called mincost tree partitioning, is introduced. In the generalized problem. the nodes of a hypergraph G are to be mapped onto the vertices of a tree structure T, and the cost function to be minimized is the cost of routing the hyperedges of G on the edges of T. The standard mincut problem is the simple case in which the tree T is a single edge connecting two vertices. Several VLSI design applications for this problem are discussed. An iterative improvement heuristic for this problem in which nodes of the hypergraph are moved between the vertices of the tree is described. The running time of a single pass of the heuristic for the unweighted version of the problem is Q(P*D*t/sup 3/), where P is the total number of pins in the hypergraph G, D is the maximum number of nodes in a hyperedge of G, and t is the number of vertices in the tree T. Several test results are discussed.
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