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» Solving iterated functions using genetic programming
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GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
15 years 9 months ago
An analysis of constructive crossover and selection pressure in genetic programming
A common problem in genetic programming search algorithms is destructive crossover in which the offspring of good parents generally has worse performance than the parents. Design...
Huayang Xie, Mengjie Zhang, Peter Andreae
139
Voted
GECCO
2010
Springer
249views Optimization» more  GECCO 2010»
15 years 5 months ago
Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach
Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
Torsten Hildebrandt, Jens Heger, Bernd Scholz-Reit...
102
Voted
CORR
2010
Springer
148views Education» more  CORR 2010»
15 years 3 months ago
Perturbation Resilience and Superiorization of Iterative Algorithms
Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there...
Yair Censor, R. Davidi, Gabor T. Herman
145
Voted
PLDI
2004
ACM
15 years 9 months ago
Fast searches for effective optimization phase sequences
It has long been known that a fixed ordering of optimization phases will not produce the best code for every application. One approach for addressing this phase ordering problem ...
Prasad Kulkarni, Stephen Hines, Jason Hiser, David...
EUROGP
2009
Springer
130views Optimization» more  EUROGP 2009»
15 years 10 months ago
One-Class Genetic Programming
One-class classification naturally only provides one-class of exemplars, the target class, from which to construct the classification model. The one-class approach is constructed...
Robert Curry, Malcolm I. Heywood