Mine Plan Optimisation

Overview

With increasing challenges in mining, both mechanically and financially, efficient mine planning and mine optimisation where possible are inevitable.
This textbook provides a range of tools for optimization in the mineral industry, including examples with mathematical programming. Topics covered include a survey of the application of optimisation technologies; a review of optimisation algorithms with math programming, math modelling and an introduction to AMPL – a widely used ...

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Overview

With increasing challenges in mining, both mechanically and financially, efficient mine planning and mine optimisation where possible are inevitable.
This textbook provides a range of tools for optimization in the mineral industry, including examples with mathematical programming. Topics covered include a survey of the application of optimisation technologies; a review of optimisation algorithms with math programming, math modelling and an introduction to AMPL – a widely used math modelling language -, applications of linear programming to business improvement studies, surface mining applications, underground mining applications and options analysis. There math programming and AMPL is supported by the www.ampl.coma and by the author’s site, www.minesmith.com.au.
This volume is intended for course use and was developed for 3rd and 4th year university education in mine planning and design or mine optimisation. Engineers, planners and policy makers in the minerals industry may find it beneficial for their professional activities as well.

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Product Details

  • ISBN-13: 9780415665780
  • Publisher: CRC Press
  • Publication date: 1/22/2015
  • Pages: 350

Table of Contents

Preface; Origin of book; Objectives of author; Outline of text; Use as an undergraduate and introductory graduate level textbook; Guidance for professional development; Acknowledgements

Introduction
1. Overview of mine planning and design
2. Levels of responsibility and decision making
3. Role of optimization in mine planning
4. Mine planning process flow
5. Influence of General Mine Planning packages
6. Optimization as practiced in the general industry
7. Optimization as a foundation for planning and design

Overview of Optimization Technology
8. Why Mathematical Programming?
9. Linear Programming
10. Integer Programming and Combinatorial Optimization
11. Solution Algorithms for Linear and Mixed Integer Programming
12. Proof of optimality
13. Review of alternative optimization methods
14. Contrast and comparison of technologies in their use and application

Survey of the application of optimization in the minerals industry
15. History of development of optimization in mine planning and design
16. Lerchs-Grossman and pit optimization
17. Linear and Mixed Integer Programming as applied to pit scheduling with extensions to Lagrange Parameterization
18. Whittle and the development of nested pit methodologies
19. Survey of research development
20. Survey of commercial applications of optimisation to mine planning
21. Gaps analysis and future trends

Introduction to mine modeling and optimization using AMPL
22. Structure of a mathematical model
23. Introduction to AMPL
24. Formulating a Linear Program
25. Network applications
26. Integer and network programming
27. Solvers
28. AMPL/Solver interaction
29. Additional learning resources for math modeling

Pit Optimization and Pushback generation
30. Formulation and solution as a Graph
31. Solution using LG
32. Formulation of the ultimate pit problem as an LP
33. Solution as a LP and unimodularity
34. Generating nested pits
35. Selecting pushbacks
36. Review of commercial applications

Open Cut Production Scheduling
37. Scheduling using math programming
38. Scheduling heuristics as applied to benches within mining stages
39. Heuristic approaches to finding a “good” schedule
40. Formulation as a MIP
41. MIP solution strategies and schedule granularity
42. MIP extensions to more complex problems
43. Sequencing and scheduling of blast masters
44. Blending, throughput and feed limitations
45. Fixed costs and capital expansion problems
46. Stockpile optimization and the cutoff problem

Underground Mine Planning
47. The process of underground mine planning
48. Using simulated annealing to define a mining inventory
49. Steiner Trees and access optimization
50. Formulation of the underground scheduling problem as a LP
51. The underground cutoff problem and overall strategy optimization
52. Converting a mining inventory into a reserve
53. Production versus activity scheduling and project management

Other Applications and Considerations
54. Strategic, tactical and operational mine planning
55. Hills of Value and option analysis using LP/MIP
56. Business-wide planning
57. Optimizing multiple business units
58. Equipment fleet and haulage optimization
59. Extensions to coal mining

Conclusions
60. Towards a discipline of mine planning
61. Gaps in the technology
62. Gaps in the profession
63. Where to from here?

Appendices
• Additional website resources
• Further readings in optimization technology
• A guide to applying AMPL to the minerals industry

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