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» Introduction to genetic programming
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PPSN
2004
Springer
15 years 3 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
GECCO
2000
Springer
225views Optimization» more  GECCO 2000»
15 years 1 months ago
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa
ENGL
2007
121views more  ENGL 2007»
14 years 9 months ago
A Comparison between Genetic Algorithms and Evolutionary Programming based on Cutting Stock Problem
—Genetic Algorithms (GA) and Evolutionary Programming (EP) are two well-known optimization methods that belong to the class of Evolutionary Algorithms (EA). Both methods have gen...
Raymond Chiong, Ooi Koon Beng
PEPM
1993
ACM
15 years 1 months ago
Binding-Time Analysis and the Taming of C Pointers
The aim of binding-time analysis is to determine when variables, expressions, statements, etc. in a program can be evaluated by classifying these into static (compile-time) and dy...
Lars Ole Andersen
GECCO
2009
Springer
166views Optimization» more  GECCO 2009»
15 years 4 months ago
Genetic programming in the wild: evolving unrestricted bytecode
We describe a methodology for evolving Java bytecode, enabling the evolution of extant, unrestricted Java programs, or programs in other languages that compile to Java bytecode. B...
Michael Orlov, Moshe Sipper