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BMCBI
2006
146views more  BMCBI 2006»
14 years 9 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
15 years 4 months ago
Evolutionary algorithms and dynamic programming
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled...
Benjamin Doerr, Anton Eremeev, Christian Horoba, F...
ECAI
2008
Springer
14 years 11 months ago
Dynamic Backtracking for Distributed Constraint Optimization
We propose a new algorithm for solving Distributed Constraint Optimization Problems (DCOPs). Our algorithm, called DyBop, is based on branch and bound search with dynamic ordering ...
Redouane Ezzahir, Christian Bessiere, Imade Benela...
CEC
2010
IEEE
14 years 10 months ago
Smart flight and dynamic tolerances in the artificial bee colony for constrained optimization
This paper presents an adaptation of a novel algorithm based on the foraging behavior of honey bees to solve constrained numerical optimization problems. The modifications focus on...
Efrén Mezura-Montes, Mauricio Damian-Araoz,...
CEC
2007
IEEE
15 years 3 months ago
Light beam search based multi-objective optimization using evolutionary algorithms
Abstract— For the past decade or so, evolutionary multiobjective optimization (EMO) methodologies have earned wide popularity for solving complex practical optimization problems,...
Kalyanmoy Deb, Abhay Kumar