loynaz 0.0.2

Compute the Approximate Edge Dominating Set for undirected graph encoded in DIMACS format.

Loynaz: Approximate Edge Dominating Set Solver

This work builds upon Efficient Edge Dominating Set Approximation for Sparse Graphs.

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Edge Dominating Set Problem - Overview

Definition

The Edge Dominating Set (EDS) problem is a classical problem in graph theory and combinatorial optimization. Given an undirected graph $G = (V, E)$, an edge dominating set is a subset $D \subseteq E$ such that every edge not in $D$ is adjacent to at least one edge in $D$.

Formal Definition:

A set $D \subseteq E$ is an edge dominating set if for every edge $e \in E \setminus D$, there exists an edge $d \in D$ such that $e$ and $d$ share a common vertex.

Objective

Find an edge dominating set $D$ of minimum cardinality (smallest possible size).

Computational Complexity

• NP-Hard: The decision version of EDS ("Does a graph $G$ have an edge dominating set of size $k$?") is NP-complete.
• Approximation: There exists a 2-approximation algorithm for EDS (i.e., a solution at most twice the optimal size).
• Exact Solutions: Solvable in exponential time via brute-force or more efficient algorithms like branch-and-bound.

Applications

• Network design and fault tolerance.
• Wireless sensor networks (efficient coverage).
• Scheduling and resource allocation problems.

Variants

• Weighted Edge Dominating Set: Edges have weights, and the goal is to minimize the total weight of $D$.
• Connected Edge Dominating Set: Requires $D$ to induce a connected subgraph.
• Efficient Edge Dominating Set: Imposes additional constraints on the structure of $D$.

Related Problems

• Vertex Cover: A vertex cover indirectly dominates edges, while EDS directly dominates them.
• Dominating Set: A vertex-based variant where vertices dominate neighboring vertices.

Example

Consider a graph $G$ with edges $E = {(1,2), (2,3), (3,4)}$:

• A minimal edge dominating set: $D = {(2,3)}$, since:
  • Edge (1,2) is adjacent to (2,3).
  • Edge (3,4) is adjacent to (2,3).

Algorithms

1. Greedy Approach: Iteratively select edges covering the most undominated edges.
2. Integer Linear Programming (ILP): Formulate EDS as an optimization problem.
3. Fixed-Parameter Tractability (FPT): Solvable in $O^*(c^k)$ time for some constant $c$.

Open Problems

• Finding improved approximation ratios or exact algorithms for special graph classes (e.g., planar graphs, bipartite graphs).
• Investigating parameterized complexity further.

References

• Garey & Johnson, Computers and Intractability (1979).
• G. F. Italiano et al., Exact and Approximate Algorithms for Edge Dominating Set.

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Problem Statement

Input: A Boolean Adjacency Matrix $M$.

Answer: Find a Minimum Edge Dominating Set.

Example Instance: 5 x 5 matrix

	c1	c2	c3	c4	c5
r1	0	0	1	0	1
r2	0	0	0	1	0
r3	1	0	0	0	1
r4	0	1	0	0	0
r5	1	0	1	0	0

The input for undirected graph is typically provided in DIMACS format. In this way, the previous adjacency matrix is represented in a text file using the following string representation:

p edge 5 4
e 1 3
e 1 5
e 2 4
e 3 5

This represents a 5x5 matrix in DIMACS format such that each edge $(v,w)$ appears exactly once in the input file and is not repeated as $(w,v)$. In this format, every edge appears in the form of

e W V

where the fields W and V specify the endpoints of the edge while the lower-case character e signifies that this is an edge descriptor line.

Example Solution:

Edge Dominating Set Found (3, 5), (2, 4): Edges (3, 5), and (2, 4) constitute an optimal solution.

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Compile and Environment

Prerequisites

• Python ≥ 3.10

Installation

pip install loynaz

Execution

1. Clone the repository:

   git clone https://github.com/frankvegadelgado/loynaz.git
   cd loynaz
   

2. Run the script:

   edge -i ./benchmarks/testMatrix1
   

   utilizing the edge command provided by Loynaz's Library to execute the Boolean adjacency matrix loynaz\benchmarks\testMatrix1. The file testMatrix1 represents the example described herein. We also support .xz, .lzma, .bz2, and .bzip2 compressed text files.

   Example Output:

   testMatrix1: Edge Dominating Set Found (3, 5), (2, 4)
   

   This indicates edges (3, 5), (2, 4) form a edge dominating set.

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Edge Dominating Set Size

Use the -c flag to count the edges in the edge dominating set:

edge -i ./benchmarks/testMatrix2 -c

Output:

testMatrix2: Edge Dominating Set Size 3

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Command Options

Display help and options:

edge -h

Output:

usage: edge [-h] -i INPUTFILE [-a] [-b] [-c] [-v] [-l] [--version]

Compute the Approximate Edge Dominating Set for undirected graph encoded in DIMACS format.

options:
  -h, --help            show this help message and exit
  -i INPUTFILE, --inputFile INPUTFILE
                        input file path
  -a, --approximation   enable comparison with a polynomial-time approximation approach within a factor of at most 2
  -b, --bruteForce      enable comparison with the exponential-time brute-force approach
  -c, --count           calculate the size of the edge dominating set
  -v, --verbose         anable verbose output
  -l, --log             enable file logging
  --version             show program's version number and exit

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Batch Execution

Batch execution allows you to solve multiple graphs within a directory consecutively.

To view available command-line options for the batch_edge command, use the following in your terminal or command prompt:

batch_edge -h

This will display the following help information:

usage: batch_edge [-h] -i INPUTDIRECTORY [-a] [-b] [-c] [-v] [-l] [--version]

Compute the Approximate Edge Dominating Set for all undirected graphs encoded in DIMACS format and stored in a directory.

options:
  -h, --help            show this help message and exit
  -i INPUTDIRECTORY, --inputDirectory INPUTDIRECTORY
                        Input directory path
  -a, --approximation   enable comparison with a polynomial-time approximation approach within a factor of at most 2
  -b, --bruteForce      enable comparison with the exponential-time brute-force approach
  -c, --count           calculate the size of the edge dominating set
  -v, --verbose         anable verbose output
  -l, --log             enable file logging
  --version             show program's version number and exit

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Testing Application

A command-line utility named test_edge is provided for evaluating the Algorithm using randomly generated, large sparse matrices. It supports the following options:

usage: test_edge [-h] -d DIMENSION [-n NUM_TESTS] [-s SPARSITY] [-a] [-b] [-c] [-w] [-v] [-l] [--version]

The Loynaz Testing Application using randomly generated, large sparse matrices.

options:
  -h, --help            show this help message and exit
  -d DIMENSION, --dimension DIMENSION
                        an integer specifying the dimensions of the square matrices
  -n NUM_TESTS, --num_tests NUM_TESTS
                        an integer specifying the number of tests to run
  -s SPARSITY, --sparsity SPARSITY
                        sparsity of the matrices (0.0 for dense, close to 1.0 for very sparse)
  -a, --approximation   enable comparison with a polynomial-time approximation approach within a factor of at most 2
  -b, --bruteForce      enable comparison with the exponential-time brute-force approach
  -c, --count           calculate the size of the edge dominating set
  -w, --write           write the generated random matrix to a file in the current directory
  -v, --verbose         anable verbose output
  -l, --log             enable file logging
  --version             show program's version number and exit

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Code

• Python implementation by Frank Vega.

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License

• MIT License.