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125
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GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 7 months ago
Combining genetic algorithms with squeaky-wheel optimization
The AI optimization algorithm called "Squeaky-Wheel Optimization" (SWO) has proven very effective in a variety of real-world applications. Although the ideas behind SWO ...
Justin Terada, Hoa Vo, David Joslin
131
Voted
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
15 years 4 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
142
Voted
CEC
2009
IEEE
15 years 10 months ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
128
Voted
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 7 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...
106
Voted
GECCO
2008
Springer
112views Optimization» more  GECCO 2008»
15 years 4 months ago
Parameter-less evolutionary search
The paper presents the parameter-less implementation of an evolutionary-based search. It does not need any predefined control parameters values, which are usually used for geneti...
Gregor Papa