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IPL
2002
65views more  IPL 2002»
15 years 6 months ago
Parallel evolutionary algorithms can achieve super-linear performance
One of the main reasons for using parallel evolutionary algorithms (PEAs) is to obtain efficient algorithms with an execution time much lower than that of their sequential counter...
Enrique Alba
GECCO
2010
Springer
189views Optimization» more  GECCO 2010»
15 years 4 months ago
Multiobjective evolutionary algorithm for software project portfolio optimization
Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering ...
Thomas Kremmel, Jirí Kubalík, Stefan...
GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
16 years 1 months ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
149
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DATE
2005
IEEE
172views Hardware» more  DATE 2005»
16 years 11 days ago
Evolutionary Optimization in Code-Based Test Compression
We provide a general formulation for the code-based test compression problem with fixed-length input blocks and propose a solution approach based on Evolutionary Algorithms. In c...
Ilia Polian, Alejandro Czutro, Bernd Becker
ADBIS
2005
Springer
100views Database» more  ADBIS 2005»
16 years 9 days ago
Evolutionary Learning of Boolean Queries by Genetic Programming
Abstract. The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its...
Suhail S. J. Owais, Pavel Krömer, Václ...