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GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
15 years 7 months ago
Exploiting gradient information in numerical multi--objective evolutionary optimization
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Peter A. N. Bosman, Edwin D. de Jong
110
Voted
CDC
2010
IEEE
154views Control Systems» more  CDC 2010»
14 years 9 months ago
Distributed constrained optimization over noisy networks
In this paper we deal with two problems which are of great interest in the field of distributed decision making and control. The first problem we tackle is the problem of achieving...
Kunal Srivastava, Angelia Nedic, Dusan M. Stipanov...
CEC
2010
IEEE
15 years 3 months ago
An analysis of massively distributed evolutionary algorithms
Computational science is placing new demands on optimization algorithms as the size of data sets and the computational complexity of scientific models continue to increase. As thes...
Travis J. Desell, David P. Anderson, Malik Magdon-...
ICCS
2003
Springer
15 years 7 months ago
A Method of Hidden Markov Model Optimization for Use with Geophysical Data Sets
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Robert A. Granat
CEC
2009
IEEE
15 years 9 months ago
Optimization of the sizing of a solar thermal electricity plant: Mathematical programming versus genetic algorithms
— Genetic algorithms (GAs) have been argued to constitute a flexible search thereby enabling to solve difficult problems which classical optimization methodologies may find ha...
Jose M. Cabello, Jose M. Cejudo, Mariano Luque, Fr...