IAES International Journal of Artificial Intelligence · 2013 · 15 citations · 7 references
Numerical AnalysisBlack Holes AlgorithmEngineeringBlack HolesBlack HoleAerospace EngineeringSwarms AlgorithmsHybrid AlgorithmFirefly AlgorithmIntelligent OptimizationSwarm AlgorithmComputer EngineeringGenetic AlgorithmHybrid Optimization TechniqueSwarm DynamicComputer ScienceComputational GeometryEvolutionary Multimodal Optimization
In this paper a swarms algorithms, for optimization problem is proposed. This algorithm is inspired of black holes. A black hole is a region of space-time whose gravitational field is so strong that nothing which enters it, not even light, can escape. Every black hole has mass, and charge. In this Algorithm we suppose each solution of problem as a black hole and use of gravity force for global search and electrical force for local search. The proposed method is verified using several benchmark problems commonly used in the area of optimization. The experimental results on different benchmarks indicate that the performance of the proposed algorithm is better than PSO (Particle Swarms Optimization), AFS (Artifitial Fish Swarm Algorithm) and RBH-PSO (random black hole particle swarm optimization Algorithm). DOI: http://dx.doi.org/10.11591/ij-ai.v2i3.3226
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Random black hole particle swarm optimization and its application
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