A Combinatorial Algorithm to Find a Maximum Even Factor

2005 ◽  
pp. 66-80 ◽  
Author(s):  
Gyula Pap
Keyword(s):  
Combinatorial Algorithm ◽  
Even Factor

scholarly journals Combinatorial approximation of maximum k-vertex cover in bipartite graphs within ratio 0.7

2018 ◽  
Vol 52 (1) ◽  
pp. 305-314 ◽  
Author(s):  
Vangelis Th. Paschos
Keyword(s):  
Greedy Algorithm ◽  
Vertex Cover ◽  
Bipartite Graphs ◽  
Approximation Ratio ◽  
Combinatorial Algorithm

We propose and analyze a simple purely combinatorial algorithm for max k-vertex cover in bipartite graphs, achieving approximation ratio 0.7. The only combinatorial algorithm currently known until now for this problem is the natural greedy algorithm, that achieves ratio (e − 1)/e = 0.632.

A Combinatorial Algorithm

1946 ◽  
Vol s1-21 (3) ◽  
pp. 219-226 ◽  
Author(s):  
Thomas E. Easterfield
Keyword(s):  
Combinatorial Algorithm

FINDING A COMBINATORIAL ALGORITHM

1979 ◽  
Vol 319 (1 Second Intern) ◽  
pp. 508-511
Author(s):  
Peter H. Sellers
Keyword(s):  
Combinatorial Algorithm

A weighted even factor algorithm

2007 ◽  
Vol 115 (2) ◽  
pp. 223-237 ◽  
Author(s):  
Kenjiro Takazawa
Keyword(s):  
Even Factor

scholarly journals Combinatorial Algorithm In Linear Model

2018 ◽  
Vol 196 ◽  
pp. 03017
Author(s):  
Jana Ižvoltová ◽  
Peter Pisca
Keyword(s):  
Parameter Estimation ◽  
Linear Model ◽  
Markov Models ◽  
Nonlinear Models ◽  
The Other ◽  
Estimation Methods ◽  
Combinatorial Algorithm ◽  
Alternative Approach ◽  
Parameter Estimation Methods ◽  
Iterative Numerical Methods

Gauss-jacobi combinatorial algorithm is an alternative approach to traditional iterative numerical methods, which is primary oriented for parameter estimation in nonlinear models. The combinatorial algorithm is often exploited for outlier diagnosis in nonlinear models, where the other parameter estimation methods lose their efficiency. The paper describes comparison of both of gauss-jacobi combinatorial and gauss-markov models executed on parameter estimation process of levelling network for the reason to find the efficiency of combinatorial algorithm in simply linear model.

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