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NC
2002
210views Neural Networks» more  NC 2002»
13 years 5 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
EMO
2009
Springer
159views Optimization» more  EMO 2009»
14 years 6 days ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
EMO
2006
Springer
172views Optimization» more  EMO 2006»
13 years 9 months ago
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen
CEC
2008
IEEE
14 years 3 days ago
Evolutionary Multi-objective Simulated Annealing with adaptive and competitive search direction
— In this paper, we propose a population-based implementation of simulated annealing to tackle multi-objective optimisation problems, in particular those of combinatorial nature....
Hui Li, Dario Landa Silva
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
13 years 11 months ago
Learned mutation strategies in genetic programming for evolution and adaptation of simulated snakebot
In this work we propose an approach of incorporating learned mutation strategies (LMS) in genetic programming (GP) employed for evolution and adaptation of locomotion gaits of sim...
Ivan Tanev