Ultimate Pit Problem with Minimum Mining Width Constraints

Long range open-pit mine planning is hard. Mining engineers and technologists tasked with developing plans in these uncertain environments are generally ill equipped to make even the simplest decisions about what material to mine and when to mine it. Operations research has historically
played an important role in providing tools and algorithms to address subproblems in this space, including the venerable ultimate pit problem originally formulated in 1965 by Lerchs and Grossmann. This presentation discusses this classic problem; first by describing the current fastest approach to solving it and then by extending it to consider highly desirable operational constraints: minimum mining width constraints.
Matthew Deutsch is a mining engineer with 10 years of experience developing software and custom algorithms for the mining
industry. He has worked at Maptek North America for 7 years
developing many tools including the Automated Pit Designer
and the Grade Control Optimizer. He is also a graduate student
at Colorado School of Mines where he is working on adding operational constraints to open-pit mine planning.

[@tchoulekojudicael4477]

Thank you Very Much sir Matthew for this wonderful presentation

[@user-il4hz1dz1b]

All currently developed algorithms of pit optimization are only the first iteration of searching for the maximum NPV of a mine project. The biggest disadvantage of these algorithm is that they model the block mine sequence form the pit bottom going up. This contradicts the mining logic. Please, keep the good work, Matthew!

[@caperio26]

Thanks Matt. Good to see more shares in topic.

[@azineha]

I need help about write meta historic algorithm in python 😢

[@user-qm7ug4hx2g]

Резкий голос, неприятный