Operating value optimization using simulation and mixed integer programming

Salama, Abubakary, Nehring, Micah and Greberg, Jenny (2013) Operating value optimization using simulation and mixed integer programming. International Journal of Mining, Reclamation and Environment, 28 1: 25-46. doi:10.1080/17480930.2013.768019


Author Salama, Abubakary
Nehring, Micah
Greberg, Jenny
Title Operating value optimization using simulation and mixed integer programming
Journal name International Journal of Mining, Reclamation and Environment   Check publisher's open access policy
ISSN 1748-0930
1748-0949
Publication date 2013-04-19
Year available 2013
Sub-type Article (original research)
DOI 10.1080/17480930.2013.768019
Volume 28
Issue 1
Start page 25
End page 46
Total pages 22
Place of publication Oxfordshire, United Kingdom
Publisher Taylor & Francis
Collection year 2014
Language eng
Abstract Mining operations around the world will increasingly need to operate at greater depths. This significantly influences the complexity of ore extraction and ore transportation to the surface. The increase in mine depth leads to increases in haulage distance from mine areas to the mine surface. This results in an increase in energy costs to haul material further. Due to the increasing cost of future operations, the choice of the haulage method becomes an important factor in the optimisation of the mine plan. The haulage process is one of the most energy intensive activities in a mining operation, and thus, one of the main contributors to energy cost. This paper presents the comparison of the operating values of the mine plans at depth levels of 1000, 2000 and 3000 m for diesel and electric trucks, shaft and belt conveyor haulage systems for the current and a predicted future energy price scenario. The aim is to analyse the impact of energy requirements associated with each haulage method, as well as the use of alternative sequencing techniques as mine depth increases. This study is carried out using a combination of discrete event simulation and mixed integer programming (MIP) as a tool to improve decision-making in the process of generating and optimising the mine plans. Results show that energy cost increases across each haulage method at both current and future energy prices, with increasing depth. This study thus provides a broad and up to date analysis of the impact on operating values that may be experienced with the use of the main haulage systems available at present. Also, the study shows how the combination of discrete event simulation and MIP generates a good tool for decision support.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 19 April 2013.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
Official 2014 Collection
 
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Created: Tue, 10 Dec 2013, 09:13:45 EST by Katie Gollschewski on behalf of School of Mechanical and Mining Engineering