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GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
16 years 1 months ago
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Gabriela Ochoa, Rong Qu, Edmund K. Burke
GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
16 years 1 months ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
GECCO
2009
Springer
100views Optimization» more  GECCO 2009»
16 years 1 months ago
Partial neighborhoods of elementary landscapes
This paper introduces a new component based model that makes it relatively simple to prove that certain types of landscapes are elementary. We use the model to reconstruct proofs ...
L. Darrell Whitley, Andrew M. Sutton
GECCO
2009
Springer
111views Optimization» more  GECCO 2009»
16 years 1 months ago
Evolving quorum sensing in digital organisms
For centuries it was thought that bacteria live asocial lives. However, recent discoveries show many species of bacteria communicate in order to perform tasks previously thought t...
Benjamin E. Beckmann, Philip K. McKinley
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
16 years 1 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria