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» An evolutionary method for complex-process optimization
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GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 1 months ago
Articulating user preferences in many-objective problems by sampling the weighted hypervolume
The hypervolume indicator has become popular in recent years both for performance assessment and to guide the search of evolutionary multiobjective optimizers. Two critical resear...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 11 months ago
Toward comparison-based adaptive operator selection
Adaptive Operator Selection (AOS) turns the impacts of the applications of variation operators into Operator Selection through a Credit Assignment mechanism. However, most Credit ...
Álvaro Fialho, Marc Schoenauer, Michè...
GECCO
2010
Springer
159views Optimization» more  GECCO 2010»
13 years 11 months ago
Evolution of division of labor in genetically homogenous groups
Within nature, the success of many organisms, including certain species of insects, mammals, slime molds, and bacteria, is attributed to their performance of division of labor, wh...
Heather Goldsby, David B. Knoester, Charles Ofria
GECCO
2010
Springer
172views Optimization» more  GECCO 2010»
13 years 11 months ago
Designing better fitness functions for automated program repair
Evolutionary methods have been used to repair programs automatically, with promising results. However, the fitness function used to achieve these results was based on a few simpl...
Ethan Fast, Claire Le Goues, Stephanie Forrest, We...
HIS
2007
13 years 8 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin