A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications
Laith Abualigah, Ali Diabat, Zong Woo Geem
Abstract
The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.
Topics & Concepts
Cluster analysisHarmony searchComputer scienceFuzzy clusteringData miningSwarm intelligenceStrengths and weaknessesArtificial intelligenceCorrelation clusteringMachine learningPattern recognition (psychology)Particle swarm optimizationPsychologySocial psychologyMetaheuristic Optimization Algorithms ResearchEnergy Efficient Wireless Sensor NetworksArtificial Immune Systems Applications