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» Evolutionary multiobjective optimization
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GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 11 months ago
Reducing the number of transistors in digital circuits using gate-level evolutionary design
This paper shows that the evolutionary design of digital circuits which is conducted at the gate level is able to produce human-competitive circuits at the transistor level. In ad...
Zbysek Gajda, Lukás Sekanina
138
Voted
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 10 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
138
Voted
GECCO
2003
Springer
108views Optimization» more  GECCO 2003»
15 years 10 months ago
Evolutionary Testing of Flag Conditions
Evolutionary Testing (ET) has been shown to be very successful in testing real world applications [16]. However, it has been pointed out [11], that further research is necessary if...
André Baresel, Harmen Sthamer
CEC
2010
IEEE
15 years 5 months ago
Behavioral diversity measures for Evolutionary Robotics
Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
Stéphane Doncieux, Jean-Baptiste Mouret
156
Voted
GECCO
2000
Springer
133views Optimization» more  GECCO 2000»
15 years 8 months ago
Hybrid Differential Evolution for Dynamic Optimization of a Fedbatch Bioreactor Process
A hybrid method of evolutionary algorithms is introduced in this study. The hybrid method includes two additional operations, acceleration and migrating operations. These two oper...
Feng-Sheng Wang