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GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
13 years 11 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
GECCO
2007
Springer
166views Optimization» more  GECCO 2007»
14 years 1 months ago
Crossover: the divine afflatus in search
The traditional GA theory is pillared on the Building Block Hypothesis (BBH) which states that Genetic Algorithms (GAs) work by discovering, emphasizing and recombining low order ...
David Iclanzan
TEC
2002
128views more  TEC 2002»
13 years 9 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
PPSN
2000
Springer
14 years 1 months ago
Optimizing through Co-evolutionary Avalanches
Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...
APIN
1998
132views more  APIN 1998»
13 years 9 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon