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GECCO
2005
Springer
109views Optimization» more  GECCO 2005»
15 years 10 months ago
A hybrid evolutionary algorithm for the p-median problem
A hybrid evolutionary algorithm (EA) for the p-median problem consist of two stages, each of which is a steady-state hybrid EA. These EAs encode selections of medians as subsets o...
István Borgulya
GECCO
2005
Springer
100views Optimization» more  GECCO 2005»
15 years 10 months ago
The MaxSolve algorithm for coevolution
Coevolution can be used to adaptively choose the tests used for evaluating candidate solutions. A long-standing question is how this dynamic setup may be organized to yield reliab...
Edwin D. de Jong
ICALP
2005
Springer
15 years 10 months ago
How Well Can Primal-Dual and Local-Ratio Algorithms Perform?
We define an algorithmic paradigm, the stack model, that captures many primal-dual and local-ratio algorithms for approximating covering and packing problems. The stack model is ...
Allan Borodin, David Cashman, Avner Magen
ICANN
2005
Springer
15 years 10 months ago
Batch-Sequential Algorithm for Neural Networks Trained with Entropic Criteria
The use of entropy as a cost function in the neural network learning phase usually implies that, in the back-propagation algorithm, the training is done in batch mode. Apart from t...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
ICCNMC
2005
Springer
15 years 10 months ago
Hierarchical Multicast Tree Algorithms for Application Layer Mesh Networks
This paper proposes a set of novel multicast algorithms for m-D mesh overlay networks that can achieve shorter multicast delay and less resource consumptions. In contrast to previo...
Weijia Jia, Wanqing Tu, Jie Wu