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GECCO
2006
Springer
178views Optimization» more  GECCO 2006»
15 years 3 months ago
Adaptively choosing niching parameters in a PSO
Niching techniques play an important role in evolutionary algorithms. Existing niching methods often require userspecified parameters, limiting their usefulness. This paper propos...
Stefan Bird, Xiaodong Li
ISCI
2006
72views more  ISCI 2006»
14 years 11 months ago
A study of particle swarm optimization particle trajectories
Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical analys...
F. Van den Bergh, Andries Petrus Engelbrecht
HIS
2007
15 years 1 months ago
New Particle Swarm Optimization Algorithm Incorporating Reproduction Operator for Solving Global Optimization Problems
This paper presents a new variant of Basic Particle Swarm Optimization (BPSO) algorithm named QI-PSO for solving global optimization problems. The QI-PSO algorithm makes use of a ...
Millie Pant, Radha Thangaraj, Ajith Abraham
ICDIM
2008
IEEE
15 years 6 months ago
Hybrid differential evolution - Particle Swarm Optimization algorithm for solving global optimization problems
This paper presents a simple, hybrid two phase global optimization algorithm called DE-PSO for solving global optimization problems. DE-PSO consists of alternating phases of Diffe...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...
IJSIR
2010
122views more  IJSIR 2010»
14 years 6 months ago
Biases in Particle Swarm Optimization
It is known that the most common versions of particle swarm optimization (PSO) algorithms are rotationally variant. It has also been pointed out that PSO algorithms can concentrat...
William M. Spears, Derek T. Green, Diana F. Spears