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» On the Brittleness of Evolutionary Algorithms
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AEI
2005
99views more  AEI 2005»
15 years 6 months 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
GECCO
2006
Springer
174views Optimization» more  GECCO 2006»
15 years 10 months ago
On the analysis of the (1+1) memetic algorithm
Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory...
Dirk Sudholt
EC
2008
157views ECommerce» more  EC 2008»
15 years 5 months ago
The Crowding Approach to Niching in Genetic Algorithms
A wide range of niching techniques have been investigated in evolutionary and genetic algorithms. In this article, we focus on niching using crowding techniques in the context of ...
Ole J. Mengshoel, David E. Goldberg
TEC
2008
88views more  TEC 2008»
15 years 6 months ago
A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
This paper describes a simulated annealing based multiobjective optimization algorithm that incorporates the concept of archive in order to provide a set of tradeoff solutions for ...
Sanghamitra Bandyopadhyay, Sriparna Saha, Ujjwal M...
SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 6 months 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