scholarly journals Efficient algorithms for the conditional covering problem

2012 ◽  
Vol 219 ◽  
pp. 39-57
Author(s):  
Robert Benkoczi ◽  
Binay Bhattacharya ◽  
Yuzhuang Hu ◽  
Chien-Hsin Lin ◽  
Qiaosheng Shi ◽  
...  
Keyword(s):  
Efficient Algorithms ◽  
Covering Problem ◽  
Conditional Covering

Algorithms for solving the conditional covering problem on paths

2005 ◽  
Vol 52 (4) ◽  
pp. 293-301 ◽  
Author(s):  
Brian J. Lunday ◽  
J. Cole Smith ◽  
Jeffrey B. Goldberg
Keyword(s):  
Covering Problem ◽  
Conditional Covering

On Conditional Covering Problem

2009 ◽  
Vol 3 (1) ◽  
pp. 97-107 ◽  
Author(s):  
Balasubramanian Sivan ◽  
S. Harini ◽  
C. Pandu Rangan
Keyword(s):  
Covering Problem ◽  
Conditional Covering

scholarly journals An Efficient Algorithm to Solve the Conditional Covering Problem on Trapezoid Graphs

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
Akul Rana ◽  
Anita Pal ◽  
Madhumangal Pal
Keyword(s):  
Time Algorithm ◽  
Chordal Graphs ◽  
Covering Problem ◽  
Shortest Distance ◽  
Trapezoid Graph ◽  
Np Complete ◽  
Conditional Covering ◽  
General Graphs ◽  
Special Case ◽  
Trapezoid Graphs

Let G=(V,E) be a simple connected undirected graph. Each vertex v∈V has a cost c(v) and provides a positive coverage radius R(v). A distance duv is associated with each edge {u,v}∈E, and d(u,v) is the shortest distance between every pair of vertices u,v∈V. A vertex v can cover all vertices that lie within the distance R(v), except the vertex itself. The conditional covering problem is to minimize the sum of the costs required to cover all the vertices in G. This problem is NP-complete for general graphs, even it remains NP-complete for chordal graphs. In this paper, an O(n2) time algorithm to solve a special case of the problem in a trapezoid graph is proposed, where n is the number of vertices of the graph. In this special case, duv=1 for every edge {u,v}∈E, c(v)=c for every v∈V(G), and R(v)=R, an integer >1, for every v∈V(G). A new data structure on trapezoid graphs is used to solve the problem.

The Maximal Conditional Covering Problem

1996 ◽  
Vol 34 (2) ◽  
pp. 77-91 ◽  
Author(s):  
Charles Revelle ◽  
Joseph Schweitzer ◽  
Stephanie Snyder
Keyword(s):  
Covering Problem ◽  
Conditional Covering

Tidal Flow: A Fast and Teachable Maximum Flow Algorithm

2018 ◽  
Vol 12 ◽  
pp. 25-41
Author(s):  
Matthew C. FONTAINE
Keyword(s):  
Computer Science ◽  
Tidal Flow ◽  
Maximum Flow ◽  
Efficient Algorithms ◽  
Science Students ◽  
Flow Algorithm ◽  
Maximum Flows

Among the most interesting problems in competitive programming involve maximum flows. However, efficient algorithms for solving these problems are often difficult for students to understand at an intuitive level. One reason for this difficulty may be a lack of suitable metaphors relating these algorithms to concepts that the students already understand. This paper introduces a novel maximum flow algorithm, Tidal Flow, that is designed to be intuitive to undergraduate andpre-university computer science students.

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