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» Guided Operators for a Hyper-Heuristic Genetic Algorithm
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AUSAI
2003
Springer
13 years 9 months ago
Guided Operators for a Hyper-Heuristic Genetic Algorithm
We have recently introduced a hyper-heuristic genetic algorithm (hyper-GA) with an adaptive length chromosome which aims to evolve an ordering of low-level heuristics so as to find...
Limin Han, Graham Kendall
CEC
2005
IEEE
13 years 6 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
IJON
2006
131views more  IJON 2006»
13 years 4 months ago
Optimizing blind source separation with guided genetic algorithms
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
J. M. Górriz, Carlos García Puntonet...
EVOW
2010
Springer
13 years 11 months ago
A Directed Mutation Operator for Real Coded Genetic Algorithms
Abstract. Developing directed mutation methods has been an interesting research topic to improve the performance of genetic algorithms (GAs) for function optimization. This paper i...
Imtiaz Korejo, Shengxiang Yang, Changhe Li
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
13 years 5 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...