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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 6 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
GECCO
2006
Springer
178views Optimization» more  GECCO 2006»
13 years 9 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
CEC
2007
IEEE
13 years 9 months ago
Development and validation of different hybridization strategies between GA and PSO
In this paper a new class of hybridization strategies between GA and PSO is presented and validated. The Genetical Swarm Optimization (GSO) approach is presented here with respect ...
A. Gandelli, F. Grimaccia, Marco Mussetta, Paola P...
ICTAI
2010
IEEE
13 years 3 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
2005
Springer
136views Optimization» more  GECCO 2005»
13 years 11 months ago
MeSwarm: memetic particle swarm optimization
In this paper, a novel variant of particle swarm optimization (PSO), named memetic particle swarm optimization algorithm (MeSwarm), is proposed for tackling the overshooting probl...
Bo-Fu Liu, Hung-Ming Chen, Jian-Hung Chen, Shiow-F...