Andreas Ernst, Mohan Krishnamoorthy, Gaurav Singh, Graham Kendall
Mine planning and scheduling is about getting the right material (quantity and quality) deposit out of the mine at the right time to the right place using the right equipment at least cost per unit of the final commodity (or product) in order to adequately fulfil the company’s business targets.
The mining industry around the world, has undergone significant changes since the turn of the century. In this time, the industry has undergone major transformations and has moved from a position of substantial strength, where the industry enjoyed one of the heftiest booms in its entire history, to a period of constantly decreasing commodity prices. This has resulted in a situation in which operational efficiency and cost savings drive thinking in what has become a considerably challenging operating environment for companies.
It is against this backdrop that this special issue will bring to focus new operations research models and algorithms that concentrate on mine efficiency optimisation.
Mining supply chains are large and complex. Moreover, the dynamics of the mining industry (lead times, geological factors and price uncertainty) means that innovative, new and specialised models and algorithms need to be developed constantly; particularly when operating margins are constantly decreasing. From an algorithmic perspective, given that most mixed integer linear programming (MILP) models tend to be large, and generally intractable, novel heuristics are employed more and more. Furthermore, today’s mining supply chains are becoming increasingly automated and are also becoming very “data-driven”. Thus, the interface between mine optimisation and scheduling models and sensors & sensor networks as well as “data science” is becoming increasingly relevant.
With all of the above in mind, a special issue will be of interest to OR and computer science academics, practitioners in the mining industry and also readers outside of the mining industry.
Potential topics to consider (but not limited to) are:
surface mining operations,
underground mining planning and scheduling models,
optimal design of mining phases (pushbacks),
mine asset maintenance and utilisation,
mine supply chain optimisation,
long term life of asset optimisation,
open pit mine scheduling,
coordination in mining supply chains,
large scale optimization,
decision making under uncertainty,
applications in cloud computing via IoT, and
case-studies in mine planning and optimisation.
Papers will need to have a direct connection with mine planning and scheduling optimisation, either via the core topic under consideration in the paper (such as asset optimisation or mining supply chain optimisation) or by novel techniques (such as, linear, integer, non-linear, convex programming, multicriteria optimisation, metaheuristics, computational geometry, statistics, etc).
The objective here is to collect all new and significant developments in mine planning and optimisation. The aim of this special issue is to present high quality papers that address recent advances in theory, practice and application in this area. The aim is to benefit researchers who are interested in this broad area by presenting the latest OR techniques and applications that are relevant to the mining industry. It is highly likely that engineers, planners and policy makers in the mining industry will also find this special issue beneficial for their professional activities.
Researchers from all relevant disciplines are invited to consider this special issue as an outlet to publish their high quality work on the topic.
All manuscripts should be submitted electronically via the Elsevier Editorial System (EES) http://ees.elsevier.com/cor.
The corresponding author must select Special Issue: Mine Planning, Scheduling and Optimisation as the Article Type to make sure that the paper will be considered for the Special Issue.
The deadline for submission to the special issue is December 15 2017.
The plan is to publish the special issue in 2018.
Prof Andreas Ernst
Department of Mathematics
Monash University, Clayton, VIC, Australia
Prof Mohan Krishnamoorthy
Department of Mechanical and Aerospace Engineering
Monash University, Clayton, VIC, Australia
Dr Gaurav Singh
Operations Research, Strategy and Innovation
BHP Billiton, Perth, WA Australia
Prof Graham Kendall
The University of Nottingham Malaysia Campus
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan