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GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
15 years 3 months ago
Two adaptive mutation operators for optima tracking in dynamic optimization problems with evolution strategies
The dynamic optimization problem concerns finding an optimum in a changing environment. In the tracking problem, the optimizer should be able to follow the optimum’s changes ov...
Claudio Rossi, Antonio Barrientos, Jaime del Cerro
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
15 years 3 months ago
Interactive evolutionary multi-objective optimization and decision-making using reference direction method
In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMO procedure to develop an algorit...
Kalyanmoy Deb, Abhishek Kumar
IJCNN
2006
IEEE
15 years 3 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
PPSN
1998
Springer
15 years 2 months ago
A Decoder-Based Evolutionary Algorithm for Constrained Parameter Optimization Problems
Several methods have been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; a survey paper [7] provides an overview of var...
Slawomir Koziel, Zbigniew Michalewicz
EUROPAR
2007
Springer
15 years 3 months ago
Locality Optimized Shared-Memory Implementations of Iterated Runge-Kutta Methods
Iterated Runge-Kutta (IRK) methods are a class of explicit solution methods for initial value problems of ordinary differential equations (ODEs) which possess a considerable poten...
Matthias Korch, Thomas Rauber