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ANOR
2007
166views more  ANOR 2007»
13 years 5 months ago
Memetic particle swarm optimization
Abstract We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in a...
Y. G. Petalas, Konstantinos E. Parsopoulos, Michae...
AMC
2007
111views more  AMC 2007»
13 years 5 months ago
Locating multiple optima using particle swarm optimization
Many scientific and engineering applications require optimization methods to find more than one solution to multimodal optimization problems. This paper presents a new particle ...
R. Brits, Andries Petrus Engelbrecht, F. Van den B...
AMC
2007
154views more  AMC 2007»
13 years 5 months ago
A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become ve...
Jing-Ru Zhang, Jun Zhang, Tat-Ming Lok, Michael R....
CEC
2007
IEEE
13 years 5 months ago
Entropy-based Memetic Particle Swarm Optimization for computing periodic orbits of nonlinear mappings
— The computation of periodic orbits of nonlinear mappings is very important for studying and better understanding the dynamics of complex systems. Evolutionary algorithms have s...
Y. G. Petalas, Konstantinos E. Parsopoulos, Michae...
DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 5 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 5 months ago
An evolutionary approach for competency-based curriculum sequencing
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
Luis de Marcos, José-Javier Martínez...
GECCO
2008
Springer
126views Optimization» more  GECCO 2008»
13 years 5 months ago
Swarm intelligence in e-learning: a learning object sequencing agent based on competencies
In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course mater...
Luis de Marcos, José-Javier Martínez...
GECCO
2008
Springer
13 years 5 months ago
Particle filtering with particle swarm optimization in systems with multiplicative noise
We propose a Particle Filter model that incorporates Particle Swarm Optimization for predicting systems with multiplicative noise. The proposed model employs a conventional multio...
A. D. Klamargias, Konstantinos E. Parsopoulos, Phi...
GECCO
2008
Springer
161views Optimization» more  GECCO 2008»
13 years 5 months ago
A new quantum behaved particle swarm optimization
This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the cha...
Millie Pant, Radha Thangaraj, Ajith Abraham
GECCO
2008
Springer
127views Optimization» more  GECCO 2008»
13 years 5 months ago
Social interaction in particle swarm optimization, the ranked FIPS, and adaptive multi-swarms
The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm’s success. In this study various approaches re...
Johannes Jordan, Sabine Helwig, Rolf Wanka