MOL Report Nine - 2017/2018

Official repository version: University of Alberta ERA

ERA DOI: 10.7939/84199

Recommended citation DOI: Use the ERA DOI above when citing this report.

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Authors: Yashar Pourrahimian; Eugene Ben-Awuah; Hooman Askari-Nasab

Contributors: Mining Optimization Laboratory (MOL) Researchers / Graduate Students

Institution: University of Alberta, Mining Optimization Laboratory (MOL)

Publication date: September 2018

ISBN: 978-1-55195-414-1  |   ERA DOI: 10.7939/84199

Previous DOI / alternate version: 10.13140/RG.2.2.34016.70401

Keywords: mine planning and design; simulation modeling of mining and industrial systems; optimization

Access: Open access / publicly available

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Abstract

MOL Report Nine (2017/2018) compiles 20 papers on surface mine planning optimization, simulation and optimization of mining systems, underground mine planning and optimization, and related mining systems research. The volume highlights mathematical programming, simulation, uncertainty modeling, and decision-support methods for mining operations.

The report includes work on geological uncertainty in block clustering, short-term production scheduling, oil sands production scheduling and waste management, truck dispatching, equipment planning, open-pit to underground transition, block caving and cut-and-fill scheduling, stope optimization, blast fragmentation effects, discrete fracture networks, and open-source frameworks for simulation database management. Together, the papers demonstrate MOL's continued emphasis on mine planning and design, simulation modeling of mining and industrial systems, and optimization.

Rights and permissions

All rights reserved, all material in this report is, unless otherwise stated, the property of the Mining Optimization Laboratory (MOL).

Reproduction or retransmission of the materials, in whole or in part, in any manner, without the prior written consent of the copyright holder, is a violation of copyright law.

The report may be circulated and disposed at your discretion; however, the following copyright notice must be adhered to.

Copyright © 2018, Mining Optimization Laboratory, University of Alberta.

Mining Optimization Laboratory sponsors may utilize and disclose the report material and software within their organization with no prior permission of MOL.

Contact information for permissions

Hooman Askari-Nasab, PhD, PEng
Professor of Mining Engineering
Department of Civil & Environmental Engineering
University of Alberta, Edmonton, AB, Canada T6G 1H9
Phone: +1 (780) 492-4053
Cell: +1 (780) 893-9365
Email: hooman@ualberta.ca
MOL Webpage: www.ualberta.ca/mol

Contributors

  1. Hooman Askari-Nasab — Professor, Director of MOL
  2. Yashar Pourrahimian — Assistant Professor, University of Alberta
  3. Eugene Ben-Awuah — Associate Professor, Laurentian University
  4. Kwame Awuah-Offei — Associate Professor, Missouri S&T
  5. Mohammad Tabesh — PhD, Research Associate (2015/09)
  6. Shiv Prakash Upadhyay — PhD, Research Associate (2016/09)
  7. Saleh Balideh — PhD, Research Associate (2016/09)
  8. Mahdi Badiozaman Tari — PhD, Research Associate (2017/12)
  9. Firouz Khodayari — PhD Student (2014/01)
  10. Ali Moradi Afrapoli — PhD Student (2014/09)
  11. Magreth Dotto — PhD Student (2018/01)
  12. Ahlam Maremi — PhD Student (2015/09)
  13. Bright Oppong Afum — PhD Student (2017/01)
  14. Emmanuel Appianing — PhD Student (2018/05)
  15. Nasib Al-Habib — PhD Student (2018/09)
  16. Alireza Kamrani — PhD Student (2018/09)
  17. Shuwei Huang — PhD Visiting Student (2017/10)
  18. Shahrokh Parvarzar — PhD Visiting Student (2018/03)
  19. Efrain Ugarte-Zarate — MSc Student (CCG) (2015/09)
  20. Zeinab Basiri — MSc Student (2016/09)
  21. Roberto Noriega — MSc Student (2017/09)
  22. Hongshuo Gong — MSc Student (2017/09)
  23. Obinna Mbadozie — MSc Student (2018/01)
  24. William Junkin — MSc Student (2018/01)

Suggested citation

Pourrahimian, Y., Ben-Awuah, E., & Askari-Nasab, H. (2018). Mining Optimization Laboratory (MOL) - Report Nine, 2017/2018. University of Alberta, Mining Optimization Laboratory (MOL). ISBN: 978-1-55195-414-1. https://doi.org/10.7939/84199