Open Pit Optimisation Using Discounted Economic Block Values

Abstract

Strategic mine planning and the management of the future cash flows are a vital core of surface mining operations. The time dimension, which is an integral part of the scheduling problem, is not embedded in traditional ultimate pit outline optimisation algorithms. This study explores the validity of the theorem that a pit outline determined by an optimal long term schedule algorithm is constrained by the conventional Lerchs and Grossmann's (LG) optimised pit outline. This hypothesis was investigated through a case study using the intelligent open pit simulator (IOPS) founded on agent based learning theories. The optimal pushback schedule was determined using IOPS before determination of the optimised final pit outline. The economic block values were discounted with respect to the allocated extraction time, followed by final pit limits optimisation using LG algorithm. © 2009 Institute of Materials.

Department(s)

Mining Engineering

Keywords and Phrases

Artificial Intelligence; Discounted Cash Flows; Mine Planning; Open Pit; Optimisation

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2009 Maney Publishing, All rights reserved.

Publication Date

01 Jan 2009

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