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Algoritmo de Lerchs-Grossmann×Sistema de Clasificación de la Masa Rocosa (RMR)×
CampoIngeniería de minasIngeniería de minas
FamiliaProcess / pipelineProcess / pipeline
Año de origen19651973
Autor originalHelmut Lerchs and Israel GrossmannZbigniew T. Bieniawski
TipoGraph-theoretic algorithm for pit limit optimizationEmpirical classification for geotechnical engineering
Fuente seminalLerchs, 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
AliasLerchs-Grossmann Method, LG AlgorithmRMR, Bieniawski Classification, RMR89
Relacionados43
ResumenThe 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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ScholarGateComparar métodos: Lerchs-Grossmann Algorithm · Rock Mass Rating. Recuperado el 2026-06-19 de https://scholargate.app/es/compare