Geodesy

Firefly algorithm

Metaheuristic

Firefly protocol

Algorithm

Benchmark (surveying)

Demography

Biology

Statistics

Canopy clustering algorithm

Local search (optimization)

Variable (mathematics)

Particle swarm optimization

Data mining

Computer science

Mathematical optimization

Mathematics

Geography

Population

Sociology

Mathematical analysis

Variable neighborhood search

CURE data clustering algorithm

Cluster analysis

Search algorithm

Correlation clustering

Zoology

Machine learning

Baghdad Science Journal

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On these bases, this work aims to improve FA using variable neighborhood search (VNS) as a local search method, providing VNS the benefit of the trade-off between the exploration and exploitation abilities. The proposed FA-VNS allows fireflies to improve the clustering solutions with the ability to enhance the clustering solutions and maintain the diversity of the clustering solutions during the search process using the perturbation operators of VNS. To evaluate the performance of the algorithm, eight benchmark datasets are utilized with four well-known clustering algorithms. The comparison according to the internal and external evaluation metrics indicates that the proposed FA-VNS can produce more compact clustering solutions than the well-known clustering algorithms.

Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering