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» Optimal Elevator Group Control by Evolution Strategies
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GECCO
2010
Springer
176views Optimization» more  GECCO 2010»
13 years 10 months ago
A hierarchical cooperative evolutionary algorithm
To successfully search multiple coadaptive subcomponents in a solution, we developed a novel cooperative evolutionary algorithm based on a new computational multilevel selection f...
Shelly Xiaonan Wu, Wolfgang Banzhaf
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 9 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...
CDC
2010
IEEE
124views Control Systems» more  CDC 2010»
13 years 3 months ago
Deployment of drifters in a piecewise-constant flow environment
We study a deployment strategy for a group of vehicles that drift in an ambient flow field. Specifically, we address the case where the flow is always greater in magnitude than an ...
Andrew Kwok, Sonia Martínez
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
13 years 9 months ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 2 months ago
Observing the swarm behaviour during its evolutionary design
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
Laura Diosan, Mihai Oltean