Mine Planning 3 - Optimization

Mine Planning 3 - Optimization

Areas of Study: Mining

Qualifies for CMS

Qualifies for Certification

This course is the third in a set of three courses on Mine Planning. The third course introduces you to mathematical optimization concepts—how these tools work and the fundamental algorithms behind them to aid the mine planning process.

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  • Audience Level:
  • Professional
  • Enrollment:
  • Required
  • Duration:
  • 20 hours

Course Summary


This course is the third in a set of three courses on Mine Planning and follows on from the previous two Mine Planning courses. Mine Planning 1 - Strategy focused on three of the five main levers for value creation as part of the strategic mine planning process (including mining method selection, process route selection and scale of operation). Mine Planning 2 - Operations then went on to illustrate the use of the final two levers including sequence and scheduling and cut-off grade policy.

Mine Planning 3 - Optimization introduces you to mathematical optimization concepts which often form the basis for many of the computerized planning tools that are commercially available today. It is important to understand how these tools work and the fundamental algorithms behind them to aid the mine planning process.


This course focuses on the use of mathematical optimization techniques and processes. Upon completion of this course, participants will be able to develop basic mathematical programming models and be able to solve this in Excel for the purpose of allocating limited resources for maximum benefit (within the mining context). Coding and scripting are beyond the scope of this course.

Assumed Background

It is assumed that participants have a fundamental knowledge of the mine planning processes and concepts that drive value and the reasons why the planning process for the exploitation of a mineral deposit is fundamentally different to that of most other industries. These concepts are discussed and illustrated in Mine Planning 1 - Strategy and Mine Planning 2 - Operations. If these concepts are not familiar, it is recommended that participants also complete these (or equivalent) courses as a sound background. It is also useful for participants to be familiar with traditional project evaluation concepts—see the Related Courses tab.

Course Content

Mine Planning 3 - Optimization consists of 8 viewing sessions with supporting figures, tables and examples, plus interactive course reviews. The concepts that are addressed in this course may not be easy to grasp at first and may require multiple revisions before a clear understanding is gained. Course participants are expected to thoroughly work through each example by hand (the aid of Microsoft Excel is encouraged) provided within the course. This may be time-consuming; however, it is integral and will ultimately allow a successful completion of the course reviews. Total course duration is equivalent to approximately 20 hours of viewing and exercise content.

Learning Outcomes

  • Identify commonly used algorithms and how they are applied in mine optimization.
  • Identify common types of linear programming problems and how they can be solved to optimize mine performance.
  • Identify alternative programming techniques and how they are applied in mine optimization.

Recommended Background

  • A degree or diploma in geology, mining or related discipline.
  • Fundamental knowledge of the mine planning processes and concepts that drive value.
  • Familiarity with traditional project evaluation concepts.

Dr. Micah Nehring Ph.D.

Micah Nehring is currently a lecturer in the Mine Planning stream of courses at The University of Queensland. His research focus is on the optimisation of mine production schedules using mathematical programming techniques. Future research will be directed toward integrating a carbon price into the optimised production scheduling process.

Prior to 2011, he worked as a lecturer and researcher at the Universidad Adolfo Ibáñez, Chile; a mine planning stream tutor at the University of Queensland; and a graduate mining engineer at Xstrata Copper Mount Isa.

Dr. Sean Shafiee Ph.D.

Sean completed his PhD in Mining Engineering with a focus on Mineral Economics and applied Real Option Valuation in mining projects through CRCMining at The University of Queensland. He has worked as an industrial consultant for Peabody Energy, Rio Tinto and Xstrata in Project Valuation and Mineral Price Modelling. He has also been actively involved in running short courses for ‘Mining Project Evaluation'. Sean completed an internship with InfoMine USA generating Australian coal cost models and comparing data from Australian coal mines to those in the USA. He has experience with the CostMine models and methodology. Sean has also published more than 15 Journal and Conference papers.

In June 2010, Sean joined JKTech as General Manager of R2Mining where he was strongly involved in the development of the CostMine Australasian business. This was a joint venture between JKTech and InfoMine.