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GECCO
2006
Springer
166views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparing genetic robustness in generational vs. steady state evolutionary algorithms
Previous research has shown that evolutionary systems not only try to develop solutions that satisfy a fitness requirement, but indirectly attempt to develop genetically robust so...
Josh Jones, Terry Soule
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
13 years 11 months ago
A hybridized genetic parallel programming based logic circuit synthesizer
Genetic Parallel Programming (GPP) is a novel Genetic Programming paradigm. Based on the GPP paradigm and a local search operator - FlowMap, a logic circuit synthesizing system in...
Wai Shing Lau, Kin-Hong Lee, Kwong-Sak Leung
GECCO
2006
Springer
164views Optimization» more  GECCO 2006»
13 years 11 months ago
Biobjective evolutionary and heuristic algorithms for intersection of geometric graphs
Wire routing in a VLSI chip often requires minimization of wire-length as well as the number of intersections among multiple nets. Such an optimization problem is computationally ...
Rajeev Kumar, Pramod Kumar Singh, Bhargab B. Bhatt...
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
13 years 11 months ago
An empirical investigation of how and why neutrality affects evolutionary search
The effects of neutrality on evolutionary search have been considered in a number of interesting studies, the results of which, however, have been contradictory. Some researchers ...
Edgar Galván López, Riccardo Poli
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
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