sleekpanther / minimum-weighted-vertex-cover-approximation-algorithm

Approximation Algorithm for the NP-Complete problem of finding a vertex cover of minimum weight in a graph with weighted vertices. Guarantees an answers at most 2 times the optimal minimum weighted vertex cover

Minimum Weighted Vertex Cover - Pricing Method (Approximation Algorithm)

Approximation Algorithm for the NP-Complete problem of finding a vertex cover of minimum weight in a graph with weighted vertices. Guarantees an answers at most 2 times the optimal minimum weighted vertex cover (2-approximation algorithm, see references for the proof).

Problem Statement

• Given an undirected graph with each vertex weighted > 0
• Find a vertex cover S ⊆ V (where each edge has at least 1 edge in S)
• And the vertex cover has the minimum total weight (when adding weights of the selected vertices)

Graph1

Graph 1 Optimal Minimum Weighted Vertex Cover

Vertex Cover = a, c
Total Weight = 4+5 = 9

Graph 1 Algorithm's Weighted Vertex Cover (sub-optimal)

Vertex Cover = a, b, d
Total Weight = 3+4+3 = 10

The algorithm does not find the optimal solution, but the answer given is 10, which is less than twice the optimal value which would be 2 * 9 = 18

Algorithm Solution

The problem is NP-Complete but this algorithm is a polynomial-time 2-approximation algorithm.
The answer found is at most 2 times the weight of the Optimal Minimum Weighted Vertex Cover.

Pricing Strategy (Fairness)

• Each edge e=(i, j) must pay a price P_e > 0 to the vertices i and j
• Fairness: an edge cannot pay more than the remaining weight of either vertex
• Tight: a vertex is tight when it has no remaining weight
  

Input Graphs

Graph 2

Graph2 Algorithm's Weighted Vertex Cover (optimal)

Vertex Cover = a, d, b
Total Weight = 2+2+4 = 8

Graph 3

Graph 3 Optimal Minimum Weighted Vertex Cover

Vertex Cover = a, c, f
Total Weight = 2+4+9 = 15

Graph 3 Algorithm's Weighted Vertex Cover (sub-optimal)

Vertex Cover = a, b, c, e
Total Weight = 2+3+4+7 = 16

Graph 4

Graph 4 Algorithm's Weighted Vertex Cover (optimal)

Vertex Cover = d, c, b
Total Weight = 1+1+1 = 3

Usage

• Create a int[] weights array
  weights[0] is the weight of vertex 0, weights[1] is the weight of vertex 1, etc.
• (Optional) Create String array for vertex names (0=a, 1=b, 2=c etc. in the example but this is arbitrary & it works as long as the underlyng graph created with integers is valid)
• Create the graph by adding undirected edges (only add each edge once)
  e.g.
  graph1.add(new Edge(0,1, vertexNames1));;
graph1.add(new Edge(0,3, vertexNames1));
  etc.
• Vertex names can be left out (A names array is created automatically if none is provided using the String representation of the integer). There's an example for graph4 which doesn't pass a names array
• The order of edges added and the names of the vertices can result in a different vertex cover
• Call MinimumWeightedVertexCover.findMinimumWeightedVertexCoverApprox(graph1, weights1, vertexNames1);

References

• Approximation Algorithms - Kevin Wayne
• BAD Vertex Cover Problem - GeeksForGeeks
  This was a terrible mistake! This algorithm is very different from the approximation algorithm and had me confused on my initial attempt

minimum-weighted-vertex-cover-approximation-algorithm's Issues

Try this :)

int vertexCount = 4;
graph1.addEdge(0,1);
graph1.addEdge(0,2);
graph1.addEdge(0,3);
int[] weights = {100, 1, 1, 1};

Common interest

Hi,
I came across your GitHub and it's quite impressive the amount of work you've put in it. I'm too am interested in Algorithms among other things like Programming Languages, Functional Programming, and Reactive Programming.
It’ll be a pleasure to connect with you on LinkedIn, but why stop there? From time to time, I'd love to compare notes and/or discuss about programming. I recently completed two algorithms courses offered by Stanford, mostly for fun, but also to jog my memory for programming interviews; what are you up to?

If you're interested, I'll be happy to talk more. I've a Gitter room https://gitter.im/sia/Lobby

https://www.linkedin.com/in/abhijit-sarkar-53161330/
https://github.com/asarkar
https://blog.asarkar.org/ (infrequent)

Regards,
Abhijit

P.S.: I assume the reason that you made these solutions public is for others to benefit from your work, but having a dozen or so repos, one for each problem, requires a lot of jumping around even for problems that are related (like approximation algorithms for NP-Complete problems). You may want to consider consolidating the various solutions into one repo for easier reference.