Sciweavers

54 search results - page 3 / 11
» Speculative Evaluation in Particle Swarm Optimization
Sort
View
GECCO
2006
Springer
178views Optimization» more  GECCO 2006»
14 years 3 days 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
2009
IEEE
14 years 3 months ago
Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes
— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
Christian L. Müller, Benedikt Baumgartner, Iv...
DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 8 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
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 1 months ago
Particle swarm hybridized with differential evolution: black box optimization benchmarking for noisy functions
In this work we evaluate a Particle Swarm Optimizer hybridized with Differential Evolution and apply it to the BlackBox Optimization Benchmarking for noisy functions (BBOB 2009)....
José García-Nieto, Enrique Alba, Jav...
GPEM
2006
127views more  GPEM 2006»
13 years 8 months ago
A hierarchical particle swarm optimizer for noisy and dynamic environments
New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
Stefan Janson, Martin Middendorf