Graph colouring using evolutionary computation: A case study of blind naked mole‐rat algorithm

Author:

Maqbool Fahad1ORCID,Fahad Muhammad1,Ilyas Muhammad1,Jabeen Hajira2

Affiliation:

1. Computer Science & IT University of Sargodha Sargodha Pakistan

2. Big Data Analytics GESIS–Leibniz Institute for the Social Sciences Cologne Germany

Abstract

AbstractGraph colouring problem (GCP) is an NP‐complete optimization problem. It is famous for its applications in scheduling, register allocation, and map colouring. In recent years, biological inspired and especially Swarm intelligence (SI) techniques have gained popularity for solving complex optimization problems. In this article, we have proposed blind naked mole rat‐based colouring (BNMR‐Col) for graphs. BNMR‐Col uses both exploitation and exploration to find the best solution in search space. Exploitation uses both local moves and global moves to find a better solution in the surroundings of an existing solution. On the other hand, exploration generates new solution by combining various solutions from the search space. BNMR‐Col shows better convergence rate and approaches the lowest colour value in 83% of the cases when tested on standard benchmark graph instances.

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Reference47 articles.

1. The effects of varying the fitness function on the efficiency of the cat Swarm optimization algorithm in solving the graph coloring problem;Bacarisas N. D.;Annals of Computer Science Series,2011

2. Solving Graph Coloring Problem Using an Enhanced Binary Dragonfly Algorithm

3. A New and Fast Evolutionary Algorithm for Strict Strong Graph Coloring Problem

4. New methods to color the vertices of a graph

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