Early start and late start algorithms to improve the solution time for long-term underground mine production scheduling

E. Topal

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

Mixed integer programming (MIP) has been used for optimizing production schedules of mines since the 1960s. The major problem in the long-term production scheduling for an entire orebody is that the number of integer variables needed to formulate an MIP model is too large to solve the formulation. This number may reach well over one hundred thousand. To overcome this difficulty, this paper presents two new algorithms to reduce the size of the problem. These algorithms assign an earliest and latest possible start date for each machine placement, eliminating the integer variables that correspond to machine placement before its early start date and after its late start date. A case study based on Kiruna Mine, the second largest underground mine in the world, is summarized in the paper. It shows substantial improvement in the solution time required using the new algorithms. This increased efficiency in the solution time of the MIP model allows it to be applied to Kiruna Mine, with the potential to increase substantially the net present value (NPV) of the project.

Original languageEnglish
Pages (from-to)99-107
Number of pages9
JournalJournal of the Southern African Institute of Mining and Metallurgy
Volume108
Issue number2
Publication statusPublished - Feb 2008
Externally publishedYes

Fingerprint

Integer programming
Scheduling

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Metals and Alloys

Cite this

@article{0d2c04111d1f4ca7b8211f1d1c9e8042,
title = "Early start and late start algorithms to improve the solution time for long-term underground mine production scheduling",
abstract = "Mixed integer programming (MIP) has been used for optimizing production schedules of mines since the 1960s. The major problem in the long-term production scheduling for an entire orebody is that the number of integer variables needed to formulate an MIP model is too large to solve the formulation. This number may reach well over one hundred thousand. To overcome this difficulty, this paper presents two new algorithms to reduce the size of the problem. These algorithms assign an earliest and latest possible start date for each machine placement, eliminating the integer variables that correspond to machine placement before its early start date and after its late start date. A case study based on Kiruna Mine, the second largest underground mine in the world, is summarized in the paper. It shows substantial improvement in the solution time required using the new algorithms. This increased efficiency in the solution time of the MIP model allows it to be applied to Kiruna Mine, with the potential to increase substantially the net present value (NPV) of the project.",
author = "E. Topal",
year = "2008",
month = "2",
language = "English",
volume = "108",
pages = "99--107",
journal = "Journal of the Southern African Institute of Mining and Metallurgy",
issn = "2225-6253",
publisher = "South African Institute of Mining and Metallurgy",
number = "2",

}

TY - JOUR

T1 - Early start and late start algorithms to improve the solution time for long-term underground mine production scheduling

AU - Topal, E.

PY - 2008/2

Y1 - 2008/2

N2 - Mixed integer programming (MIP) has been used for optimizing production schedules of mines since the 1960s. The major problem in the long-term production scheduling for an entire orebody is that the number of integer variables needed to formulate an MIP model is too large to solve the formulation. This number may reach well over one hundred thousand. To overcome this difficulty, this paper presents two new algorithms to reduce the size of the problem. These algorithms assign an earliest and latest possible start date for each machine placement, eliminating the integer variables that correspond to machine placement before its early start date and after its late start date. A case study based on Kiruna Mine, the second largest underground mine in the world, is summarized in the paper. It shows substantial improvement in the solution time required using the new algorithms. This increased efficiency in the solution time of the MIP model allows it to be applied to Kiruna Mine, with the potential to increase substantially the net present value (NPV) of the project.

AB - Mixed integer programming (MIP) has been used for optimizing production schedules of mines since the 1960s. The major problem in the long-term production scheduling for an entire orebody is that the number of integer variables needed to formulate an MIP model is too large to solve the formulation. This number may reach well over one hundred thousand. To overcome this difficulty, this paper presents two new algorithms to reduce the size of the problem. These algorithms assign an earliest and latest possible start date for each machine placement, eliminating the integer variables that correspond to machine placement before its early start date and after its late start date. A case study based on Kiruna Mine, the second largest underground mine in the world, is summarized in the paper. It shows substantial improvement in the solution time required using the new algorithms. This increased efficiency in the solution time of the MIP model allows it to be applied to Kiruna Mine, with the potential to increase substantially the net present value (NPV) of the project.

UR - http://www.scopus.com/inward/record.url?scp=41849090769&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=41849090769&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:41849090769

VL - 108

SP - 99

EP - 107

JO - Journal of the Southern African Institute of Mining and Metallurgy

JF - Journal of the Southern African Institute of Mining and Metallurgy

SN - 2225-6253

IS - 2

ER -