Graph Partitioning for Independent Sets

02/05/2015
by   Sebastian Lamm, et al.
0

Computing maximum independent sets in graphs is an important problem in computer science. In this paper, we develop an evolutionary algorithm to tackle the problem. The core innovations of the algorithm are very natural combine operations based on graph partitioning and local search algorithms. More precisely, we employ a state-of-the-art graph partitioner to derive operations that enable us to quickly exchange whole blocks of given independent sets. To enhance newly computed offsprings we combine our operators with a local search algorithm. Our experimental evaluation indicates that we are able to outperform state-of-the-art algorithms on a variety of instances.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/29/2022

Finding Near-Optimal Weight Independent Sets at Scale

Computing maximum weight independent sets in graphs is an important NP-h...
research
03/28/2022

A Metaheuristic Algorithm for Large Maximum Weight Independent Set Problems

Motivated by a real-world vehicle routing application, we consider the m...
research
02/20/2018

Memetic Graph Clustering

It is common knowledge that there is no single best strategy for graph c...
research
04/05/2021

Reformulating DOVER-Lap Label Mapping as a Graph Partitioning Problem

We recently proposed DOVER-Lap, a method for combining overlap-aware spe...
research
08/28/2023

Parallel Unconstrained Local Search for Partitioning Irregular Graphs

We present new refinement heuristics for the balanced graph partitioning...
research
02/06/2017

Distributed Evolutionary k-way Node Separators

Computing high quality node separators in large graphs is necessary for ...
research
04/20/2012

A Fast and Effective Local Search Algorithm for Optimizing the Placement of Wind Turbines

The placement of wind turbines on a given area of land such that the win...

Please sign up or login with your details

Forgot password? Click here to reset