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GECCO
2009
Springer
174views Optimization» more  GECCO 2009»
13 years 7 months ago
Shape grammars and grammatical evolution for evolutionary design
We describe the first steps in the adoption of Shape Grammars with Grammatical Evolution for application in Evolutionary Design. Combining the concepts of Shape Grammars and Genet...
Michael O'Neill, John Mark Swafford, James McDermo...
GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
14 years 3 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
CEC
2009
IEEE
14 years 4 months ago
A clustering multi-objective evolutionary algorithm based on orthogonal and uniform design
Abstract— Designing efficient algorithms for difficult multiobjective optimization problems is a very challenging problem. In this paper a new clustering multi-objective evolut...
Yuping Wang, Chuangyin Dang, Hecheng Li, Lixia Han...
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
14 years 3 months ago
Exploring selection mechanisms for an agent-based distributed evolutionary algorithm
In this paper we propose an agent-based model of evolutionary algorithms (EAs) which extends seamlessly from concurrent single-host to distributed multi-host installations. Since ...
A. E. Eiben, Marc Schoenauer, Juan Luís Jim...
EVOW
2008
Springer
13 years 11 months ago
A Memory Enhanced Evolutionary Algorithm for Dynamic Scheduling Problems
Abstract. This paper describes a memory enhanced evolutionary algorithm (EA) approach to the dynamic job shop scheduling problem. Memory enhanced EAs have been widely investigated ...
Gregory J. Barlow, Stephen F. Smith