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Scaling Algorithms for Network Problems
, 1985
"... This paper gives algorithms for network problems that work by scaling the numeric parameters. Assume all parameters are integers. Let n, m, and N denote the number of vertices, number of edges, and largest parameter of the network, respectively. A scaling algorithm for maximum weight matching on a b ..."
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Cited by 76 (2 self)
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This paper gives algorithms for network problems that work by scaling the numeric parameters. Assume all parameters are integers. Let n, m, and N denote the number of vertices, number of edges, and largest parameter of the network, respectively. A scaling algorithm for maximum weight matching on a bipartite graph runs in O(n3 % log N) time. For appropriate N this improves the traditional Hungarian method, whose most efftcient implementation is O(n(m + n log n)). The speedup results from finding augmenting paths in batches. The matching algorithm gives similar improvements for the following problems: singlesource shortest paths for arbitrary edge lengths (Bellman’s algorithm); maximum weight degreeconstrained subgraph; minimum cost flow on a cl network. Scaling gives a simple maximum value flow algorithm that matches the best known bound (Sleator and Tarjan’s algorithm) when log N = O(log n). Scaling also gives a good algorithm for shortest paths on a directed graph with nonnegative edge lengths (Dijkstra’s algorithm).
New Dynamic Algorithms for Shortest Path Tree Computation
 IEEE/ACM Transactions on Networking
, 2000
"... The OSPF and ISIS routing protocols widely used in today's Internet compute a shortest path tree (SPT) from each router to other routers in a routing area. Many existing commercial routers recompute an SPT from scratch following changes in the link states of the network. Such recomputation of ..."
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Cited by 75 (1 self)
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The OSPF and ISIS routing protocols widely used in today's Internet compute a shortest path tree (SPT) from each router to other routers in a routing area. Many existing commercial routers recompute an SPT from scratch following changes in the link states of the network. Such recomputation of an entire SPT is inecient and may consume a considerable amount of CPU time. Moreover, as there may coexist multiple SPTs in a network with a set of given link states, recomputation from scratch causes frequent unnecessary changes in the topology of an existing SPT and may lead to routing instability. In this paper, we present new dynamic SPT algorithms that make use of the structure of the previously computed SPT. Besides efficiency, our algorithm design objective is to achieve routing stability by making minimum changes to the topology of an existing SPT (while maintaining shortest path property) when some link states in the network have changed. We establish an algorithmic framework that allows ...
Scaling algorithms for the shortest paths problem
 In SODA ’93: Proceedings of the fourth annual ACMSIAM Symposium on Discrete algorithms
, 1993
"... Abstract. We describe a new method for designing scaling algorithms for the singlesource shortest paths problem and use this method to obtain an O (Vcfftn log N) algorithm for the problem. (Here n and m are the number of nodes and arcs in the input network and N is essentially the absolute value of ..."
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Cited by 74 (6 self)
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Abstract. We describe a new method for designing scaling algorithms for the singlesource shortest paths problem and use this method to obtain an O (Vcfftn log N) algorithm for the problem. (Here n and m are the number of nodes and arcs in the input network and N is essentially the absolute value of the most negative arc length; arc lengths are assumed to be integral.) This improves previous bounds for the problem. The method extends to related problems. Key words, shortest paths problem, graph theory, networks, scaling AMS subject classifications. 68Q20, 68Q25, 68R10, 05C70 1. Introduction. In
Planar Graphs, Negative Weight Edges, Shortest Paths, and Near Linear Time
 In Proc. 42nd IEEE Annual Symposium on Foundations of Computer Science
, 2001
"... for finding shortest paths in a planar graph with real weights. ..."
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Cited by 69 (0 self)
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for finding shortest paths in a planar graph with real weights.
Shortest Path Algorithms in Transportation Models: Classical and Innovative Aspects
, 1998
"... Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is transportation, where shortest path problems of different kinds need to be solved. Due to the nature of the application, transportation scientists ..."
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Cited by 67 (3 self)
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Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is transportation, where shortest path problems of different kinds need to be solved. Due to the nature of the application, transportation scientists need very flexible and efficient shortest path procedures, both from the running time point of view, and also for the memory requirements. Since no "best" algorithm currently exists for every kind of transportation problem, research in this field has recently moved to the design and implementation of "ad hoc" shortest path procedures, which are able to capture the peculiarities of the problems under consideration. The aim of this work is to present in a unifying framework both the main algorithmic approaches that have been proposed in the past years for solving the shortest path problems arising most frequently in the transportation field, and also some important implementation techniques ...
2D Euclidean distance transform algorithms: A comparative survey
 ACM COMPUTING SURVEYS
, 2008
"... The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this wo ..."
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Cited by 63 (5 self)
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The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, stateoftheart sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.
Adaptive AgentDriven Routing and Load Balancing in Communication Networks
 Advances in Complex Systems
, 1998
"... This paper presents an unified overview of a new family of distributed algorithms for routing and load balancing in dynamic communication networks. These new algorithms are described as an extension to the classical routing algorithms: they combine the ideas of online asynchronous distance vector ro ..."
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Cited by 62 (0 self)
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This paper presents an unified overview of a new family of distributed algorithms for routing and load balancing in dynamic communication networks. These new algorithms are described as an extension to the classical routing algorithms: they combine the ideas of online asynchronous distance vector routing with adaptive link state routing. Estimates of the current traffic condition and link costs are measured by sending routing agents in the network that mix with the regular information packets and keep track of the costs (e.g. delay) encountered during their journey. The routing tables are then regularly updated based on that information without any central control nor complete knowledge of the network topology. Two new algorithms are proposed here. The first one is based on round trip routing agents that update the routing tables by backtracking their way after having reached the destination. The second one relies on forward agents that update the routing tables directly as they move t...
Minimization Algorithms for Sequential Transducers
, 2000
"... We present general algorithms for minimizing sequential finitestate transducers that output strings or numbers. The algorithms are shown to be efficient since in the case of acyclic transducers and for output strings they operate in O(S+E+V+(EV+F)x(Pmax+1)) steps, where S is the sum of ..."
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Cited by 62 (11 self)
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We present general algorithms for minimizing sequential finitestate transducers that output strings or numbers. The algorithms are shown to be efficient since in the case of acyclic transducers and for output strings they operate in O(S+E+V+(EV+F)x(Pmax+1)) steps, where S is the sum of the lengths of all output labels of the resulting transducer, E the set of transitions of the given transducer, V the set of its states, F the set of final states, and Pmax one of the longest of the longest common prefixes of the output paths leaving each state of the transducer. The algorithms apply to a larger class of transducers which includes subsequential transducers.
NegativeCycle Detection Algorithms
 MATHEMATICAL PROGRAMMING
, 1996
"... We study the problem of finding a negative length cycle in a network. An algorithm for the negative cycle problem combines a shortest path algorithm and a cycle detection strategy. We study various combinations of shortest path algorithms and cycle detection strategies and find the best combinations ..."
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Cited by 60 (5 self)
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We study the problem of finding a negative length cycle in a network. An algorithm for the negative cycle problem combines a shortest path algorithm and a cycle detection strategy. We study various combinations of shortest path algorithms and cycle detection strategies and find the best combinations. One of our discoveries is that a cycle detection strategy of Tarjan greatly improves practical performance of a classical shortest path algorithm, making it competitive with the fastest known algorithms on a wide range of problems. As a part of our study, we develop problem families for testing negative cycle algorithms.
Adaptive leastexpected time paths in stochastic, timevarying transportation and data networks
 Networks
"... In congested transportation and data networks, travel (or transmission) times are timevarying quantities that are at best known a priori with uncertainty. In such stochastic, timevarying (or STV) networks, one can choose to use the a priori leastexpected time (LET) path or one can make improved r ..."
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Cited by 54 (0 self)
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In congested transportation and data networks, travel (or transmission) times are timevarying quantities that are at best known a priori with uncertainty. In such stochastic, timevarying (or STV) networks, one can choose to use the a priori leastexpected time (LET) path or one can make improved routing decisions en route as traversal times on traveled arcs are experienced and arrival times at intermediate locations are revealed. In this context, for a given origin–destination pair at a specific departure time, a single path may not provide an adequate solution, because the optimal path depends on intermediate information concerning experienced traversal times on traveled arcs. Thus, a set of strategies, referred to as hyperpaths, are generated to provide directions to the destination node conditioned upon arrival times at intermediate locations. In this paper, an efficient labelsettingbased algorithm is presented for determining the adaptive LET hyperpaths in STV networks. Such a procedure is useful in making critical routing decisions in Intelligent Transportation Systems (ITS) and data communication networks. A sidebyside comparison of this procedure with a labelcorrectingbased algorithm for solving the same problem is made. Results of extensive computational tests to assess and compare the performance of both algorithms, as well as to investigate the characteristics of the resulting hyperpaths, are presented. An illustrative example of both procedures is provided. © 2001 John Wiley & Sons, Inc.