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GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 8 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
CEC
2007
IEEE
13 years 9 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
13 years 11 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
GECCO
2006
Springer
146views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolutionary motion design for humanoid robots
We propose a new approach to generating the motion of humanoid robots intuitively by means of Interactive Evolutionary Computation (IEC). In our system, novice users are able to d...
Toshihiko Yanase, Hitoshi Iba
BIBE
2008
IEEE
14 years 2 months ago
Robust parameter identification for biological circuit calibration
Abstract-The aim of this work is to compare some deterministic optimization algorithms and evolutionary algorithms on parameter estimation in a biological circuit design problem: t...
Giuseppe Nicosia, Eva Sciacca