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Lerchs-Grossmannin algoritmi×Kallion lujuusluokitus (RMR)×
TieteenalaKaivostekniikkaKaivostekniikka
MenetelmäperheProcess / pipelineProcess / pipeline
Syntyvuosi19651973
KehittäjäHelmut Lerchs and Israel GrossmannZbigniew T. Bieniawski
TyyppiGraph-theoretic algorithm for pit limit optimizationEmpirical classification for geotechnical engineering
AlkuperäislähdeLerchs, H., & Grossmann, I. F. (1965). Optimum design of open-pit mines. Canadian Mining and Metallurgical Bulletin, 58(633), 47-54. link ↗Bieniawski, Z. T. (1989). Engineering rock mass classifications. John Wiley & Sons. ISBN: 978-0-471-60437-4
RinnakkaisnimetLerchs-Grossmann Method, LG AlgorithmRMR, Bieniawski Classification, RMR89
Liittyvät43
TiivistelmäThe Lerchs-Grossmann Algorithm is a graph-theoretic method for determining the ultimate pit limit in open-pit mining operations. Introduced by Helmut Lerchs and Israel Grossmann in 1965, it maximizes the net present value of extracted ore while respecting slope stability constraints. This algorithm forms the theoretical foundation for most modern pit optimization software.The Rock Mass Rating (RMR) system, developed by Zbigniew Bieniawski starting in 1973, is an empirical classification that characterizes rock mass quality and estimates mining and civil engineering behavior. RMR combines five measurable geotechnical parameters into a single index ranging from 0 to 100, where higher values indicate stronger, more stable rock masses. It is the most widely used rock classification system worldwide for underground mining design.
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ScholarGateVertaile menetelmiä: Lerchs-Grossmann Algorithm · Rock Mass Rating. Haettu 2026-06-19 osoitteesta https://scholargate.app/fi/compare