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» Genetic algorithm optimization of superresolution parameters
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GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 5 months ago
Rotated test problems for assessing the performance of multi-objective optimization algorithms
This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multiobjective Optimization) algorithms on their ability in dealin...
Antony W. Iorio, Xiaodong Li
GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
15 years 7 months ago
A scalable parallel genetic algorithm for x-ray spectroscopic analysis
We use a parallel multi-objective genetic algorithm to drive a search and reconstruction spectroscopic analysis of plasma gradients in inertial confinement fusion (ICF) implosion...
Kai Xu, Sushil J. Louis, Roberto C. Mancini
121
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AAAI
2000
15 years 3 months ago
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...
BMCBI
2010
185views more  BMCBI 2010»
14 years 8 months ago
MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heu
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...
Raphaël Helaers, Michel C. Milinkovitch
GECCO
2004
Springer
15 years 7 months ago
Limit Cycle Prediction in Multivariable Nonlinear Systems Using Genetic Algorithms
Abstract. This paper presents an intelligent method based on multiuobjective genetic algorithm (MOGA) for prediction of limit cycle in multivariable nonlinear systems. First we add...
Farzan Rashidi, Mehran Rashidi