Results 11  20
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698
Almost all kcolorable graphs are easy to color
 In: J. Algorithms
, 1988
"... We describe a simple and e cient heuristic algorithm for the graph coloring problem and show that for all k it nds an optimal coloring for almost all kcolorable graphs We also show that an algorithm proposed by Brelaz and justi ed on experimental grounds optimally colors almost all kcolorable gr ..."
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Cited by 72 (0 self)
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graphs E cient implementations of both algorithms are given The rst one runs in O
nm log k time where n is the number of vertices and m the number of edges The new implementation of Brelazs algorithm runs in O
m logn time We observe that the popular greedy heuristic works poorly on kcolorable graphs
Deterministic O(nm) Time EdgeSplitting in Undirected Graphs
 J. Combinatorial Optimization
, 1997
"... This paper presents a deterministic O(nm log n + n 2 log 2 n) = ~ O(nm) time algorithm for splitting o all edges incident to a vertex s of even degree in a multigraph G, where n and m are the numbers of vertices and links (= vertex pairs between which G has an edge) in G, respectively. Based o ..."
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Cited by 11 (4 self)
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This paper presents a deterministic O(nm log n + n 2 log 2 n) = ~ O(nm) time algorithm for splitting o all edges incident to a vertex s of even degree in a multigraph G, where n and m are the numbers of vertices and links (= vertex pairs between which G has an edge) in G, respectively. Based
2 (N;m; p) Networks
"... window algorithm for the multicast Log 2 ( 0) network and expressed a desire to see its extension to the Log 2 ( ) network. Later, Kabacinski and Danilewicz generalized the fixedsize window to variable size to improve the results. In this paper, we further extend the variablesize results from the ..."
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window algorithm for the multicast Log 2 ( 0) network and expressed a desire to see its extension to the Log 2 ( ) network. Later, Kabacinski and Danilewicz generalized the fixedsize window to variable size to improve the results. In this paper, we further extend the variablesize results from
Fluid Flow, Temperature Logs
"... Temperature logs at 18 drillholes in the four large Roadside rock piles at the molybdenum mine near Questa, NM, allow the fitting of equations representing heat transfer to temperature data, providing estimates of vertical and horizontal flow. From firstorder approximations, the analyses indicate ..."
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Temperature logs at 18 drillholes in the four large Roadside rock piles at the molybdenum mine near Questa, NM, allow the fitting of equations representing heat transfer to temperature data, providing estimates of vertical and horizontal flow. From firstorder approximations, the analyses indicate
Improved Time Bounds for the Maximum Flow Problem
, 1987
"... A Recently, Goldberg proposed a new approach to the maximum network flow problem. The approach yields a very simple algorithm running in O(n) "time on nvertex networks. Incorporation of the dynamic tree data structure of Sleator and Tarjan yields a more complicated algorithm with a running ti ..."
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Cited by 48 (11 self)
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time of O(nm log (n2/m)) on medge netvorks.'Ahuja and Orlin developedIa variant of GoldbeWrs algorithm, that uses scaling and runs in O(nm + h2 logU) time on networks with integer edge capacities bounded by U. * this paper w. t obtaina modification of the AhujaOrlin algorithm with a running
A Fast and Simple Algorithm for the Maximum Flow Problem
 OPERATIONS RESEARCH
, 1989
"... We present a simple sequential algorithm for the maximum flow problem on a network with n nodes, m arcs, and integer arc capacities bounded by U. Under the practical assumption that U is polynomially bounded in n, our algorithm runs in time O(nm + n 2 log n). This result improves the previous best b ..."
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Cited by 43 (8 self)
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We present a simple sequential algorithm for the maximum flow problem on a network with n nodes, m arcs, and integer arc capacities bounded by U. Under the practical assumption that U is polynomially bounded in n, our algorithm runs in time O(nm + n 2 log n). This result improves the previous best
A polynomial time primal network simplex algorithm for minimum cost flows
, 1995
"... Developing a polynomial time algorithm for the minimum cost flow problem has been a long standing open problem. In this paper, we develop one such algorithm that runs in O(min(n 2 m log nC, n 2 m 2 log n)) time, where n is the number of nodes in the network, m is the number of arcs, and C denotes th ..."
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Cited by 37 (1 self)
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if each arc directed towards the root has a nonpositive reduced cost and each arc directed away from the root has a nonnegative reduced cost. We then develop a costscaling version of the premultiplier algorithm that solves the minimum cost flow problem in O(min(nm log nC, nm 2 log n)) pivots
Average Grain Radius (nm) Simulation
"... Summary The deformation of nanograined metals is explored from three aspects: computation under a recently developed microstructural evolution algorithm; mechanics modelling for the cooperative insertionrotation process under the 9grain cluster model; and molecular dynamics simulation for fast is ..."
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steps of grain neighbor switching. Numerical simulations based on these principles are given for a representing cell composed of 200 nonuniform grains. The deformation process is portrayed in the snapshots shown in the left of Fig. 1, while the straight line in the loglog plot on the right indicates
Can a Maximum Flow be Computed in o(nm) Time?
 IN PROC. ICALP
, 1990
"... We show that a maximum flow in a network with n vertices can be computed deterministically in O(n³/log n) time on a uniformcost RAM. For dense graphs, this improves the previous best bound of O(n³). The bottleneck in our algorithm is a combinatorial problem on (unweighted) graphs. The number of op ..."
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Cited by 18 (0 self)
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of operations executed on flow variables is O(nS/3(log n)4/3), in contrast with f~(nm) flow operations for all previous algorithms, where m denotes the number of edges in the network. A randomized version of our algorithm executes O(nal2rn 1/2 (log n) 312 + n 2 (log n) 2) flow operations with high probability
Use of dynamic trees in a network simplex algorithm for the maximum flow problem
, 1991
"... Goldfarb and Hao (1990) have proposed a pivot rule for the primal network simplex algorithm that will solve a maximum flow problem on an nvertex, marc network in at most nm pivots and O(n²m) time. In this paper we describe how to extend the dynamic tree data structure of Sleator and Tarjan (1983, ..."
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Cited by 28 (4 self)
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, 1985) to reduce the running time of this algorithm to O(nm log n). This bound is less than a logarithmic factor larger than those of the fastest known algorithms for the problem. Our extension of dynamic trees is interesting in its own right and may well have additional applications.
Results 11  20
of
698