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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
9 years 8 months ago
Integrating user preferences with particle swarms for multi-objective optimization
This paper proposes a method to use reference points as preferences to guide a particle swarm algorithm to search towards preferred regions of the Pareto front. A decision maker c...
Upali K. Wickramasinghe, Xiaodong Li
ANTSW
2006
Springer
9 years 10 months ago
Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour
The particle swarm algorithm contains elements which map fairly strongly to the foraging problem in behavioural ecology. In this paper, we show how some simple adaptions to the sta...
Cecilia Di Chio, Riccardo Poli, Paolo Di Chio
CEC
2008
IEEE
10 years 1 months ago
On the scalability of particle swarm optimisation
— Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution...
Sébastien Piccand, Michael O'Neill, Jacquel...
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