A Parallel Genetic Algorithm for Generalized Vertex Cover Problem
arXiv:1411.7612v19 citations
Originality Synthesis-oriented
AI Analysis
This work addresses a specific combinatorial optimization problem for researchers and practitioners, but it is incremental as it applies an existing method to a new framework.
The paper tackles the generalized vertex cover problem by developing a parallel genetic algorithm using Hadoop MapReduce, resulting in faster computation times on multiple machines.
This paper presents a parallel genetic algorithm for generalised vertex cover problem (GVCP) using Hadoop Map-Reduce framework. The proposed Map-Reduce implementation helps to run the genetic algorithm for generalized vertex cover problem (GVCP) on multiple machines parallely and computes the solution in relatively short time.