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128
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GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 8 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
132
Voted
GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
15 years 8 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
130
Voted
GECCO
2004
Springer
15 years 8 months ago
Limit Cycle Prediction in Multivariable Nonlinear Systems Using Genetic Algorithms
Abstract. This paper presents an intelligent method based on multiuobjective genetic algorithm (MOGA) for prediction of limit cycle in multivariable nonlinear systems. First we add...
Farzan Rashidi, Mehran Rashidi
ATS
2000
IEEE
98views Hardware» more  ATS 2000»
15 years 7 months ago
Embedded core testing using genetic algorithms
Testing of embedded cores is very difficult in SOC (system-on-a-chip), since the core user may not know the gate level implementation of the core, and the controllability and obse...
Ruofan Xu, Michael S. Hsiao
123
Voted
GECCO
1999
Springer
15 years 6 months ago
Terrain-Based Genetic Algorithm (TBGA): Modeling Parameter Space as Terrain
The Terrain-Based Genetic Algorithm (TBGA) is a self-tuning version of the traditional Cellular Genetic Algorithm (CGA). In a TBGA, various combinations of parameter values appear...
V. Scott Gordon, Rebecca Pirie, Adam Wachter, Scot...