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» Entropy-Driven Parameter Control for Evolutionary Algorithms
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GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 8 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»
15 years 11 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»
15 years 9 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»
15 years 9 months 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»
15 years 5 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