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125
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ICTAI
2006
IEEE
15 years 10 months ago
Intelligent Optimization via Learnable Evolution Model
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....
GECCO
2005
Springer
107views Optimization» more  GECCO 2005»
15 years 9 months ago
Minimum spanning trees made easier via multi-objective optimization
Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate t...
Frank Neumann, Ingo Wegener
AAAI
2000
15 years 5 months ago
Applying Learnable Evolution Model to Heat Exchanger Design
A new approach to evolutionary computation, called Learnable Evolution Model (LEM), has been applied to the problem of optimizing tube structures of heat exchangers. In contrast t...
Kenneth A. Kaufman, Ryszard S. Michalski
182
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FPL
2010
Springer
188views Hardware» more  FPL 2010»
15 years 1 months ago
SeqHive: A Reconfigurable Computer Cluster for Genome Re-sequencing
We demonstrate how Field Programmable Gate Arrays (FPGAs) may be used to address the computing challenges associated with assembling genome sequences from recent ultra-high-through...
Kristian Stevens, Henry Chen, Terry Filiba, Peter ...
128
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ICCSA
2005
Springer
15 years 9 months ago
Evolutionary Algorithm for Congestion Problem in Connection-Oriented Networks
The major objective of this paper is to deploy an effective evolutionary algorithm (EA) for the congestion problem in connection-oriented networks. The network flow is modeled as n...
Michal Przewozniczek, Krzysztof Walkowiak