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

Graph 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.