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» GP Echo Subsumption = Improved Problem Solving
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GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
13 years 10 months ago
CGP visits the Santa Fe trail: effects of heuristics on GP
GP uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees, and GP searches t...
Cezary Z. Janikow, Christopher J. Mann
GECCO
2010
Springer
249views Optimization» more  GECCO 2010»
13 years 6 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...
GPEM
2006
97views more  GPEM 2006»
13 years 4 months ago
Evolving recursive programs by using adaptive grammar based genetic programming
Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software ree...
Man Wong
GECCO
2008
Springer
129views Optimization» more  GECCO 2008»
13 years 6 months ago
Exploiting the path of least resistance in evolution
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
Gearoid Murphy, Conor Ryan
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 6 months ago
Subheuristic search and scalability in a hyperheuristic
Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics ar...
Robert E. Keller, Riccardo Poli