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A Factor 2 Approximation Algorithm for the Generalized Steiner Network Problem
 Combinatorica
"... We present a factor 2 approximation algorithm for finding a minimumcost subgraph having at least a specified number of edges in each cut. This class of problems includes, among others, the generalized Steiner network problem, which is also known as the survivable network design problem. Our algorit ..."
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Cited by 270 (3 self)
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We present a factor 2 approximation algorithm for finding a minimumcost subgraph having at least a specified number of edges in each cut. This class of problems includes, among others, the generalized Steiner network problem, which is also known as the survivable network design problem. Our
Conventional 2approximation Algorithm to the Collapsing Knapsack Problem
"... We show that the conventional 2approximation algorithm for the classical 0–1 knapsack problem does not work for the collapsing knapsack problem in general. We also show that the algorithm will work for the problem under some special conditions. Keywords: Combinatorial Optimization; Collapsing Knaps ..."
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We show that the conventional 2approximation algorithm for the classical 0–1 knapsack problem does not work for the collapsing knapsack problem in general. We also show that the algorithm will work for the problem under some special conditions. Keywords: Combinatorial Optimization; Collapsing
An Exponential Time 2Approximation Algorithm for Bandwidth
"... The bandwidth of a graph G on n vertices is the minimum b such that the vertices of G can be labeled from 1 to n such that the labels of every pair of adjacent vertices differ by at most b. In this paper, we present a 2approximation algorithm for the Bandwidth problem that takes worstcase O(1.9797 ..."
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Cited by 5 (0 self)
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The bandwidth of a graph G on n vertices is the minimum b such that the vertices of G can be labeled from 1 to n such that the labels of every pair of adjacent vertices differ by at most b. In this paper, we present a 2approximation algorithm for the Bandwidth problem that takes worstcase O(1
A local 2approximation algorithm for the vertex cover problem
 IN PROC. 23RD SYMPOSIUM ON DISTRIBUTED COMPUTING (DISC 2009), VOLUME 5805 OF LNCS
, 2009
"... We present a distributed 2approximation algorithm for the minimum vertex cover problem. The algorithm is deterministic, and it runs in (∆ + 1)² synchronous communication rounds, where ∆ is the maximum degree of the graph. For ∆ = 3, we give a 2approximation algorithm also for the weighted version ..."
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Cited by 14 (11 self)
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We present a distributed 2approximation algorithm for the minimum vertex cover problem. The algorithm is deterministic, and it runs in (∆ + 1)² synchronous communication rounds, where ∆ is the maximum degree of the graph. For ∆ = 3, we give a 2approximation algorithm also for the weighted
A 3/2approximation algorithm for sorting by reversals
 Proceedings of the 9th Annual ACMSIAM Symposium on Discrete Algorithms
, 1998
"... The description of reversal graphs given in [1] is incorrect. The following modifications should be made. Give black edges of the cycle graph G(π) a direction from π(i) to π(i+1). For a particular black edge (π(i), π(i + 1)), the tail is π(i) and the head is π(i + 1). Change the definitions of orien ..."
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Cited by 39 (0 self)
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The description of reversal graphs given in [1] is incorrect. The following modifications should be made. Give black edges of the cycle graph G(π) a direction from π(i) to π(i+1). For a particular black edge (π(i), π(i + 1)), the tail is π(i) and the head is π(i + 1). Change the definitions of oriented and unoriented cycles of G(π) as follows: A cycle is unoriented if every grey edge in the cycle connects the head of a black edge to the tail of a black edge. Otherwise a cycle is oriented. Change the definition of the reversal graph R(C) as follows: For each pair of adjacent elements in π that are not connected by a black edge in the cycle graph, introduce an isolated blue vertex 1. For each grey edge g in G(π) introduce a vertex vg. Vertex vg is coloured blue if g is part of a cycle C in C in which g connects the head of a black edge to the tail of a black edge. Otherwise vg is coloured red. (The edges of the graph are defined in the same way as before.) Change the way that a reversal ρ(u) affects the cycle graph as follows: Let u be a vertex of R(C) that arises from cycle C. If u is blue then after applying ρ(u), do not remove any black or grey edges from the resulting cycle graph. 1 Below we change the cycle graph so that sometimes elements that form an adjacency are still connected by a black edge.
2Approximation Algorithm for Finding a Spanning Tree with Maximum Number of Leaves
 Lect. Notes Comput. Sci
, 1998
"... . We study the problem of finding a spanning tree with maximum number of leaves. We present a simple 2approximation algorithm for the problem, improving on the approximation ratio of 3 achieved by the best previous algorithms. We also study the variant in which a given set of vertices must be leave ..."
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Cited by 36 (0 self)
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. We study the problem of finding a spanning tree with maximum number of leaves. We present a simple 2approximation algorithm for the problem, improving on the approximation ratio of 3 achieved by the best previous algorithms. We also study the variant in which a given set of vertices must
2−Approximation Algorithm for a Generalized, Multiple Depot Hamiltonian Path Problem
, 2007
"... We consider a Generalized, Multiple Depot Hamiltonian Path Problem (GMDHPP) and show that it has an algorithm with an approximation ratio of 32 if the costs are symmetric and satisfy the triangle inequality. This improves on the 2approximation algorithm already available for the same. ..."
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We consider a Generalized, Multiple Depot Hamiltonian Path Problem (GMDHPP) and show that it has an algorithm with an approximation ratio of 32 if the costs are symmetric and satisfy the triangle inequality. This improves on the 2approximation algorithm already available for the same.
2Approximation Algorithm for Parallel Machine Scheduling with Consecutive Eligibility
, 2003
"... We consider the problem of scheduling n jobs on m machines with the objective of minimizing makespan. Each job cannot be eligible to all the machines but to its consecutively eligible set of machines. For this problem, a 2approximation algorithm, MFFH, is developed. In addition, an example is prese ..."
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We consider the problem of scheduling n jobs on m machines with the objective of minimizing makespan. Each job cannot be eligible to all the machines but to its consecutively eligible set of machines. For this problem, a 2approximation algorithm, MFFH, is developed. In addition, an example
A 2approximation algorithm for the undirected feedback vertex set problem
 SIAM J. Discrete Math
, 1999
"... Abstract. A feedback vertex set of a graph is a subset of vertices that contains at least one vertex from every cycle in the graph. The problem considered is that of finding a minimum feedback vertex set given a weighted and undirected graph. We present a simple and efficient approximation algorithm ..."
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Cited by 92 (0 self)
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algorithm with performance ratio of at most 2, improving previous best bounds for either weighted or unweighted cases of the problem. Any further improvement on this bound, matching the best constant factor known for the vertex cover problem, is deemed challenging. The approximation principle, underlying
A fast 2approximation algorithm for the minimum Manhattan network problem
 In Proceedings of the 4th International Conference on Algorithmic Aspects in Information Management
, 2008
"... Abstract. Given a set T of n points in IR 2, a Manhattan Network G is a network with all its edges horizontal or vertical segments, such that for all p,q ∈ T, in G there exists a path (named a Manhattan path) of the length exactly the Manhattan distance between p and q. The Minimum Manhattan Network ..."
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Cited by 5 (2 self)
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Network (MMN) problem is to find a Manhattan network of the minimum length, i.e., the total length of the segments of the network is to be minimized. In this paper we present a 2approximation algorithm with time complexity O(n 2), which improves the 2approximation algorithm with time complexity Ω(n 8
Results 1  10
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1,202,825