Calibration of Genetic Algorithm Parameters for Mining-Related Optimization Problems

Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on the selection of the GA parameter values (crossover and mutation rates and population size). We propose an approach based on full factorial and...

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Veröffentlicht in:	Natural resources research (New York, N.Y.) Jg. 28; H. 2; S. 443 - 456
Hauptverfasser:	Villalba Matamoros, Martha E., Kumral, Mustafa
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2019 Springer Nature B.V
Schlagworte:	Algorithms Calibration Chemistry and Earth Sciences Computer Science Computing time Crossovers Earth and Environmental Science Earth Sciences Fossil Fuels (incl. Carbon Capture) Genetic algorithms Geography Heuristic methods Mathematical Modeling and Industrial Mathematics Mineral Resources Mutation Mutation rates Objective function Optimization Original Paper Parameters Physics Population number Response surface methodology Statistics for Engineering Sustainable Development Underground mines Underground mine planning Genetic algorithms (GA) Stope layout optimization Response surface methodology GA parameters
ISSN:	1520-7439, 1573-8981
Online-Zugang:	Volltext
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