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FGCS
2006
82views more  FGCS 2006»
13 years 8 months ago
PGGA: A predictable and grouped genetic algorithm for job scheduling
This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimati...
Maozhen Li, Bin Yu, Man Qi
ENGL
2007
121views more  ENGL 2007»
13 years 8 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
GECCO
2009
Springer
200views Optimization» more  GECCO 2009»
14 years 3 months ago
Optimization of the trading rule in foreign exchange using genetic algorithm
The generation of profitable trading rules for Foreign Exchange (FX) investments is a difficult but popular problem. The use of Machine Learning in this problem allows us to obtai...
Akinori Hirabayashi, Claus de Castro Aranha, Hitos...
GECCO
2009
Springer
144views Optimization» more  GECCO 2009»
14 years 3 months ago
A hybrid genetic algorithm for a variant of two-dimensional packing problem
A variant of two-dimensional packing problem was given in the GECCO’2008 competition. This paper describes the genetic algorithm that produced the best result and thus won the N...
Jin Kim, Byung Ro Moon
CEC
2008
IEEE
14 years 3 months ago
Solving deceptive problems using a genetic algorithm with reserve selection
— Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global o...
Yang Chen, Jinglu Hu, Kotaro Hirasawa, Songnian Yu