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GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
14 years 3 months ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
14 years 2 months ago
Evolutionary optimization of dynamic control problems accelerated by progressive step reduction
In this paper, we describe the use of an evolutionary algorithm (EA) to solve dynamic control optimization problems in engineering. In this class of problems, a set of control var...
Q. Tuan Pham
EVOW
2005
Springer
14 years 2 months ago
Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems
Abstract. Evolutionary algorithms are powerful tools in search and optimization tasks with several applications in complex engineering problems. However, setting all associated par...
Marcos H. Maruo, Heitor S. Lopes, Myriam Regattier...
PATAT
2004
Springer
141views Education» more  PATAT 2004»
14 years 2 months ago
A Hybrid Multi-objective Evolutionary Algorithm for the Uncapacitated Exam Proximity Problem
A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the tr...
Pascal Côté, Tony Wong, Robert Sabour...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
14 years 1 months ago
Application of a simple binary genetic algorithm to a noiseless testbed benchmark
One of the earliest evolutionary computation algorithms, the genetic algorithm, is applied to the noise-free BBOB 2009 testbed. It is adapted to the continuous domain by increasin...
Miguel Nicolau