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» Entropy-Driven Parameter Control for Evolutionary Algorithms
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GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
A comparative study of evolutionary optimization techniques in dynamic environments
Genetic Algorithms have widely been used for solving optimization problems in stationary environments. In recent years, there has been a growing interest for investigating and imp...
Demet Ayvaz, Haluk Topcuoglu, Fikret S. Gürge...
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
14 years 1 months ago
An online implementable differential evolution tuned optimal guidance law
This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engag...
Raghunathan Thangavelu, S. Pradeep
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 5 days ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
EOR
2007
77views more  EOR 2007»
13 years 7 months ago
Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach
In this paper, we introduce an adaptive evolutionary approach to solve the short-term electrical generation scheduling problem (STEGS). The STEGS is a hard constraint satisfaction...
Jorge Maturana, María-Cristina Riff