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EMO
2006
Springer
170views Optimization» more  EMO 2006»
14 years 23 days ago
Robust Multi-Objective Optimization in High Dimensional Spaces
1 In most real world optimization problems several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in Multi-Objective Optim...
André Sülflow, Nicole Drechsler, Rolf ...
ICGA
1997
122views Optimization» more  ICGA 1997»
13 years 10 months ago
A Comparison of Global and Local Search Methods in Drug Docking
Molecular docking software makes computational predictions of the interaction of molecules. This can be useful, for example, in evaluating the binding of candidate drug molecules ...
Christopher D. Rosin, R. Scott Halliday, William E...
GECCO
2011
Springer
261views Optimization» more  GECCO 2011»
13 years 17 days ago
Spacing memetic algorithms
We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space dista...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
GECCO
2010
Springer
248views Optimization» more  GECCO 2010»
14 years 15 days ago
Integrating decision space diversity into hypervolume-based multiobjective search
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Tamara Ulrich, Johannes Bader, Eckart Zitzler
GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
14 years 2 months ago
Breeding swarms: a new approach to recurrent neural network training
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
Matthew Settles, Paul Nathan, Terence Soule