An improved particle swarm optimization algorithm with adaptive weighted delay velocity
Lin Xu, Baoye Song, Maoyong Cao
Abstract
An improved particle swarm optimization (PSO) with adaptive weighted delay velocity (PSO-AWDV) is proposed in this paper. A new scheme blending weighted delay velocity is firstly presented for a new PSO with weighted delay velocity (PSO-WDV) algorithm. Then, to adaptively update the velocity inertia weight, an adaptive PSO-AWDV algorithm is developed based on the evolutionary state of the particle swarm evaluated via a new estimation method. The newly proposed adaptive PSO-AWDV algorithm is tested based on some famous benchmark functions, which can confirm that the performance of PSO-AWDV is superior to several well-known PSO variants and intelligent optimization algorithms in literature.
Topics & Concepts
Particle swarm optimizationBenchmark (surveying)InertiaAlgorithmMathematical optimizationMulti-swarm optimizationSwarm behaviourMathematicsScheme (mathematics)Control theory (sociology)Computer scienceArtificial intelligencePhysicsMathematical analysisGeodesyGeographyControl (management)Classical mechanicsMetaheuristic Optimization Algorithms ResearchAdvanced Algorithms and ApplicationsEvolutionary Algorithms and Applications