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94
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CEC
2008
IEEE
15 years 7 months ago
Parallel multi-objective optimization using Master-Slave model on heterogeneous resources
Abstract— In this paper, we study parallelization of multiobjective optimization algorithms on a set of hetergeneous resources based on the Master-Slave model. Master-Slave model...
Sanaz Mostaghim, Jürgen Branke, Andrew Lewis,...
96
Voted
AEI
2005
99views more  AEI 2005»
15 years 22 days ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson
139
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SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 22 days ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
151
Voted
TFS
2008
157views more  TFS 2008»
15 years 8 days ago
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Cheng-Jian Lin, Cheng-Hung Chen, Chin-Teng Lin
TEC
2010
112views more  TEC 2010»
14 years 7 months ago
Population-Based Algorithm Portfolios for Numerical Optimization
In this paper, we consider the scenario that a population-based algorithm is applied to a numerical optimization problem and a solution needs to be presented within a given time bu...
Fei Peng, Ke Tang, Guoliang Chen, Xin Yao