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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 11 (1994), S. 278-290 
    ISSN: 1432-0541
    Keywords: Network flow ; Cuts ; Parametric cuts ; Graph algorithms ; Layout
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Galloet al. [4] recently examined the problem of computing on line a sequence ofk maximum flows and minimum cuts in a network ofn nodes, where certain edge capacities change between each flow. They showed that for an important class of networks, thek maximum flows and minimum cuts can be computed simply in O(n3+kn2) total time, provided that the capacity changes are made “in order.” Using dynamic trees their time bound isO(nm log(n2/m)+km log(n2/m)). We show how to reduce the total time, using a simple algorithm, to O(n3+kn) for explicitly computing thek minimum cuts and implicitly representing thek flows. Using dynamic trees our bound is O(nm log(n2/m)+kn log(n2/m)). We further reduce the total time toO(n 2√m) ifk is at most O(n). We also apply the ideas from [10] to show that the faster bounds hold even when the capacity changes are not “in order,” provided we only need the minimum cuts; if the flows are required then the times are respectively O(n3+km) and O(n2√m). We illustrate the utility of these results by applying them to therectilinear layout problem.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 7 (1992), S. 499-519 
    ISSN: 1432-0541
    Keywords: Graph algorithms ; Combinatorial optimization ; Network flow ; Parametric optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Many combinatorial optimization problems are solved by a sequence of network flow computations on a network whose edge capacities are given as a function of a parameter λ. Recently Galloet al. [7] made a major advance in solving such parametric flow problems. They showed that for an important class of networks, calledmonotone parametric flow networks, a sequence ofO(n) flow computations could be solved in the same worst-case time bound as a single flow. However, these results require one of two special assumptions: either that the λ values are presented in increasing or decreasing order; or that the edge capacity functions are affine functions of λ. In this paper we show how to remove both of these assumptions while obtaining the same running times as in [7]. This observation generalizes and unifies the two major results of [7], and allows its ideas to be applied to many new combinatorial problems. Of greatest importance, it allows the efficient application of binary search and successive binary search to a sequence of network flow problems.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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