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GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 1 months ago
Observing the swarm behaviour during its evolutionary design
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
Laura Diosan, Mihai Oltean
CEC
2009
IEEE
14 years 2 months ago
An adaptive learning particle swarm optimizer for function optimization
— Traditional particle swarm optimization (PSO) suffers from the premature convergence problem, which usually results in PSO being trapped in local optima. This paper presents an...
Changhe Li, Shengxiang Yang
ICTAI
2010
IEEE
13 years 5 months ago
Metropolis Particle Swarm Optimization Algorithm with Mutation Operator for Global Optimization Problems
When a local optimal solution is reached with classical Particle Swarm Optimization (PSO), all particles in the swarm gather around it, and escaping from this local optima becomes...
Lhassane Idoumghar, M. Idrissi-Aouad, Mahmoud Melk...
GECCO
2009
Springer
153views Optimization» more  GECCO 2009»
14 years 10 days ago
An evaporation mechanism for dynamic and noisy multimodal optimization
Dealing with imprecise information is a common characteristic in real-world problems. Specifically, when the source of the information are physical sensors, a level of noise in t...
Jose Luis Fernandez-Marquez, Josep Lluís Ar...
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 10 days ago
Particle swarm hybridized with differential evolution: black box optimization benchmarking for noisy functions
In this work we evaluate a Particle Swarm Optimizer hybridized with Differential Evolution and apply it to the BlackBox Optimization Benchmarking for noisy functions (BBOB 2009)....
José García-Nieto, Enrique Alba, Jav...