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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
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Combinatorica 15 (1995), S. 425-434 
    ISSN: 1439-6912
    Keywords: 68 Q 25 ; 68 R 10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper we consider the worst case ratio between the capacity of min-cuts and the value of max-flow for multicommodity flow problems. We improve the best known bounds for the min-cut max-flow ratio for multicommodity flows in undirected graphs, by replacing theO(logD) in the bound byO(logk), whereD denotes the sum of all demands, andk demotes the number of commodities. In essence we prove that up to constant factors the worst min-cut max-flow ratios appear in problems where demands are integral and polynomial in the number of commodities. Klein, Rao, Agrawal, and Ravi have previously proved that if the demands and the capacities are integral, then the min-cut max-flow ratio in general undirected graphs is bounded byO(logClogD), whereC denotes the sum of all the capacities. Tragoudas has improved this bound toO(lognlogD), wheren is the number of nodes in the network. Garg, Vazirani and Yannakakis further improved this toO(logklogD). Klein, Plotkin and Rao have proved that for planar networks, the ratio isO(logD). Our result improves the bound for general networks toO(log2 k) and the bound for planar networks toO(logk). In both cases our result implies the first non-trivial bound that is independent of the magnitude of the numbers involved. The method presented in this paper can be used to give polynomial time approximation algorithms to the minimum cuts in the network up to the above factors.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 42 (1988), S. 489-563 
    ISSN: 1436-4646
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Polyhedra related to matroids and sub- or supermodular functions play a central role in combinatorial optimization. The purpose of this paper is to present a unified treatment of the subject. The structure of generalized polymatroids and submodular flow systems is discussed in detail along with their close interrelation. In addition to providing several applications, we summarize many known results within this general framework.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 62 (1993), S. 461-474 
    ISSN: 1436-4646
    Keywords: Approximation algorithms ; generalized assignment problem ; scheduling unrelated parallel machines
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The generalized assignment problem can be viewed as the following problem of scheduling parallel machines with costs. Each job is to be processed by exactly one machine; processing jobj on machinei requires timep ij and incurs a cost ofc ij ; each machinei is available forT i time units, and the objective is to minimize the total cost incurred. Our main result is as follows. There is a polynomial-time algorithm that, given a valueC, either proves that no feasible schedule of costC exists, or else finds a schedule of cost at mostC where each machinei is used for at most 2T i time units. We also extend this result to a variant of the problem where, instead of a fixed processing timep ij , there is a range of possible processing times for each machine—job pair, and the cost linearly increases as the processing time decreases. We show that these results imply a polynomial-time 2-approximation algorithm to minimize a weighted sum of the cost and the makespan, i.e., the maximum job completion time. We also consider the objective of minimizing the mean job completion time. We show that there is a polynomial-time algorithm that, given valuesM andT, either proves that no schedule of mean job completion timeM and makespanT exists, or else finds a schedule of mean job completion time at mostM and makespan at most 2T.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 60 (1993), S. 255-276 
    ISSN: 1436-4646
    Keywords: Strongly polynomial ; dual simplex algorithm ; network simplex algorithm ; minimum cost network flows
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We show how to use polynomial and strongly polynomial capacity scaling algorithms for the transshipment problem to design a polynomial dual network simplex pivot rule. Our best pivoting strategy leads to an O(m 2 logn) bound on the number of pivots, wheren andm denotes the number of nodes and arcs in the input network. If the demands are integral and at mostB, we also give an O(m(m+n logn) min(lognB, m logn))-time implementation of a strategy that requires somewhat more pivots.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 46 (1990), S. 259-271 
    ISSN: 1436-4646
    Keywords: Scheduling ; parallel machines ; approximation algorithm ; worst case analysis ; linear programming ; integer programming ; rounding
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We consider the following scheduling problem. There arem parallel machines andn independent jobs. Each job is to be assigned to one of the machines. The processing of jobj on machinei requires timep ij . The objective is to find a schedule that minimizes the makespan. Our main result is a polynomial algorithm which constructs a schedule that is guaranteed to be no longer than twice the optimum. We also present a polynomial approximation scheme for the case that the number of machines is fixed. Both approximation results are corollaries of a theorem about the relationship of a class of integer programming problems and their linear programming relaxations. In particular, we give a polynomial method to round the fractional extreme points of the linear program to integral points that nearly satisfy the constraints. In contrast to our main result, we prove that no polynomial algorithm can achieve a worst-case ratio less than 3/2 unlessP = NP. We finally obtain a complexity classification for all special cases with a fixed number of processing times.
    Type of Medium: Electronic Resource
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