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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 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
GECCO
2003
Springer
163views Optimization» more  GECCO 2003»
14 years 17 days ago
Swarms in Dynamic Environments
Charged particle swarm optimization (CPSO) is well suited to the dynamic search problem since inter-particle repulsion maintains population diversity and good tracking can be achie...
T. M. Blackwell
EVOW
2007
Springer
14 years 1 months ago
Triggered Memory-Based Swarm Optimization in Dynamic Environments
In recent years, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are t...
Hongfeng Wang, Dingwei Wang, Shengxiang Yang
CEC
2008
IEEE
14 years 1 months ago
Solving large scale global optimization using improved Particle Swarm Optimizer
—As more and more real-world optimization problems become increasingly complex, algorithms with more capable optimizations are also increasing in demand. For solving large scale ...
Sheng-Ta Hsieh, Tsung-Ying Sun, Chan-Cheng Liu, Sh...
ESCIENCE
2006
IEEE
14 years 1 months ago
Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization
This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two p...
David Ireland, Andrew Lewis, Sanaz Mostaghim, Junw...