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TEC
2008
135views more  TEC 2008»
13 years 5 months ago
Quantum Genetic Optimization
Abstract--The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to varying fitness f...
Andrea Malossini, Enrico Blanzieri, T. Calarco
GECCO
2000
Springer
106views Optimization» more  GECCO 2000»
13 years 8 months ago
A Genetic Segmentation Algorithm for Image Data Streams and Video
We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical gene...
Patrick Chiu, Andreas Girgensohn, Wolfgang Polak, ...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
13 years 10 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
13 years 10 months ago
Multi-niche crowding in the development of parallel genetic simulated annealing
In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from ...
Zhi-Gang Wang, Mustafizur Rahman 0002, Yoke-San Wo...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 6 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed