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EUROGP
2005
Springer
15 years 7 months ago
Understanding Evolved Genetic Programs for a Real World Object Detection Problem
We describe an approach to understanding evolved programs for a real world object detection problem, that of finding orthodontic landmarks in cranio-facial X-Rays. The approach in...
Victor Ciesielski, Andrew Innes, Sabu John, John M...
89
Voted
IJCAI
1993
15 years 3 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
123
Voted
EVOW
2001
Springer
15 years 6 months ago
An Evolutionary Annealing Approach to Graph Coloring
This paper presents a new heuristic algorithm for the graph coloring problem based on a combination of genetic algorithms and simulated annealing. Our algorithm exploits a novel cr...
Dimitris Fotakis, Spiridon D. Likothanassis, Stama...
GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
15 years 2 months ago
Crossover can provably be useful in evolutionary computation
We show that the natural evolutionary algorithm for the all-pairs shortest path problem is significantly faster with a crossover operator than without. This is the first theoret...
Benjamin Doerr, Edda Happ, Christian Klein
CEC
2009
IEEE
15 years 8 months ago
When is an estimation of distribution algorithm better than an evolutionary algorithm?
—Despite the wide-spread popularity of estimation of distribution algorithms (EDAs), there has been no theoretical proof that there exist optimisation problems where EDAs perform...
Tianshi Chen, Per Kristian Lehre, Ke Tang, Xin Yao