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» Rank based variation operators for genetic algorithms
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CEC
2007
IEEE
14 years 1 months ago
A cost benefit operator for efficient multi level genetic algorithm searches
— In this paper we present a novel cost benefit operator that assists multi level genetic algorithm searches. Through the use of the cost benefit operator, it is possible to dyna...
George G. Mitchell, Barry McMullin, James Decraene
AE
2007
Springer
14 years 1 months ago
A Study of Crossover Operators for Gene Selection of Microarray Data
Classification of microarray data requires the selection of a subset of relevant genes in order to achieve good classification performance. Several genetic algorithms have been d...
Jose Crispin Hernandez Hernandez, Béatrice ...
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
14 years 1 months ago
A genetic algorithm for unmanned aerial vehicle routing
Genetic Algorithms (GAs) can efficiently produce high quality results for hard combinatorial real world problems such as the Vehicle Routing Problem (VRP). Genetic Vehicle Represe...
Matthew A. Russell, Gary B. Lamont
DMIN
2007
91views Data Mining» more  DMIN 2007»
13 years 9 months ago
Instance Ranking using Ensemble Spread
- This paper investigates a technique for predicting ensemble uncertainty originally proposed in the weather forecasting domain. The overall purpose is to find out if the technique...
Rikard König, Ulf Johansson, Lars Niklasson
ECAL
2005
Springer
14 years 1 months ago
On the Mean Convergence Time of Multi-parent Genetic Algorithms Without Selection
This paper investigates genetic drift in multi-parent genetic algorithms (MPGAs). An exact model based on Markov chains is proposed to formulate the variation of gene frequency. Th...
Chuan-Kang Ting