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ENGL
2007
121views more  ENGL 2007»
13 years 6 months ago
A Comparison between Genetic Algorithms and Evolutionary Programming based on Cutting Stock Problem
—Genetic Algorithms (GA) and Evolutionary Programming (EP) are two well-known optimization methods that belong to the class of Evolutionary Algorithms (EA). Both methods have gen...
Raymond Chiong, Ooi Koon Beng
ICML
2009
IEEE
14 years 1 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
14 years 3 days ago
Convergence Examples of a Filter-Based Evolutionary Algorithm
Abstract. We describe and critique the convergence properties of filterbased evolutionary pattern search algorithms (F-EPSAs). F-EPSAs implicitly use a filter to perform a multi-...
Lauren M. Clevenger, William E. Hart
GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
13 years 7 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
BMVC
1998
13 years 8 months ago
A Method for Dynamic Clustering of Data
This paper describes a method for the segmentation of dynamic data. It extends well known algorithms developed in the context of static clustering (e.g., the c-means algorithm, Ko...
Arnaldo J. Abrantes, Jorge S. Marques