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GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
13 years 6 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya
GECCO
2008
Springer
147views Optimization» more  GECCO 2008»
13 years 6 months ago
On selecting the best individual in noisy environments
In evolutionary algorithms, the typical post-processing phase involves selection of the best-of-run individual, which becomes the final outcome of the evolutionary run. Trivial f...
Wojciech Jaskowski, Wojciech Kotlowski
NC
2002
210views Neural Networks» more  NC 2002»
13 years 4 months ago
Recent approaches to global optimization problems through Particle Swarm Optimization
This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detectin...
Konstantinos E. Parsopoulos, Michael N. Vrahatis
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
13 years 10 months ago
Fitness inheritance for noisy evolutionary multi-objective optimization
This paper compares the performance of anti-noise methods, particularly probabilistic and re-sampling methods, using NSGA2. It then proposes a computationally less expensive appro...
Lam Thu Bui, Hussein A. Abbass, Daryl Essam
GPEM
2006
127views more  GPEM 2006»
13 years 4 months ago
A hierarchical particle swarm optimizer for noisy and dynamic environments
New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
Stefan Janson, Martin Middendorf