Mining Goes Digital – Mueller et al. (Eds)
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
357
Improvements in plan-driven truck dispatching systems
for surface mining
M. Samavati, A.W. Palmer, A.J. Hill & K.M. Seiler
Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia
ABSTRACT: Truck dispatching systems have been widely used since the 1970s for truck
assignments in open pit mines, in order to coordinate material movement from diggers to process
plants and stockpiles. Existing commercial solutions are commonly plan-driven systems, which
operate by making real-time truck assignments while maintaining conformance to an established haulage allocation plan. Such systems typically comprise programming models to determine the allocation plan as a set of material flow rates. A significant limitation of these methods
is that they optimise flow rates only for instantaneous production. These approaches ignore
upcoming events and changes in availability and performance, limiting the ability to optimise
flows around such events. The method proposed in this paper extends existing approaches by
modelling material flows over a future time-horizon, incorporating upcoming events, disruptions, and changes in resources. Results are presented comparing an established algorithm with
the proposed method, showing improved handling of disruption events.
1 INTRODUCTION
Over half of the operating costs of open-pit mines can come from operating the fleet of
haul trucks (Alarie and Gamache 2002). Consequently, haul truck dispatching methods that
optimally utilise the fleet inside an open pit are of great interest to mining companies. Haul
truck dispatching in an open pit mine is the process of coordinating material movement from
diggers to process plants and stockpiles, through assigning trucks. Since the 1970s, computerbased truck dispatching systems have been widely used for this purpose. Existing approaches
can be classified into: rule-driven heuristics, constrained-assignment approaches, and plandriven approaches (Munirathinam and Yingling 1994).
Existing commercial solutions in the mining industry are commonly plan-driven systems,
operating by making real-time truck assignments while maintaining conformance to an established haulage allocation plan. These systems consist of two components: the haulage allocation
component and the dispatching component (Munirathinam and Yingling 1994). The haulage
allocation component designs an allocation plan as a set of material flow rates from diggers to
process plants and stockpiles, e.g., kilograms per second of material from a particular digger
to specific dumps (i.e., plants and stockpiles). Such plans are designed in a way that the production targets of the company for a certain time horizon (e.g., a 12-hour shift or 24 hours)
are fulfilled subject to the operational constraints. Given that the mineral deposit is broken
into smaller segments, or blocks, the company’s targets are often the amount of material that
must be extracted from certain blocks and sent to certain dumps. The dispatching component
attempts to achieve the allocation plan through assigning individual haul trucks to haul routes.
This paper focuses on the haulage allocation component. A variety of methods have been
developed to generate optimal flow rates, often comprising a linear programming model. However, a significant limitation of these methods is that they optimise flow rates only for instantaneous production, and do not have an awareness of the production target for the entire
time horizon. They are also unable to plan around upcoming disruptions, such as planned
maintenance and breaks, or changes in equipment availability (e.g., changes in the number of
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
357
Improvements in plan-driven truck dispatching systems
for surface mining
M. Samavati, A.W. Palmer, A.J. Hill & K.M. Seiler
Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia
ABSTRACT: Truck dispatching systems have been widely used since the 1970s for truck
assignments in open pit mines, in order to coordinate material movement from diggers to process
plants and stockpiles. Existing commercial solutions are commonly plan-driven systems, which
operate by making real-time truck assignments while maintaining conformance to an established haulage allocation plan. Such systems typically comprise programming models to determine the allocation plan as a set of material flow rates. A significant limitation of these methods
is that they optimise flow rates only for instantaneous production. These approaches ignore
upcoming events and changes in availability and performance, limiting the ability to optimise
flows around such events. The method proposed in this paper extends existing approaches by
modelling material flows over a future time-horizon, incorporating upcoming events, disruptions, and changes in resources. Results are presented comparing an established algorithm with
the proposed method, showing improved handling of disruption events.
1 INTRODUCTION
Over half of the operating costs of open-pit mines can come from operating the fleet of
haul trucks (Alarie and Gamache 2002). Consequently, haul truck dispatching methods that
optimally utilise the fleet inside an open pit are of great interest to mining companies. Haul
truck dispatching in an open pit mine is the process of coordinating material movement from
diggers to process plants and stockpiles, through assigning trucks. Since the 1970s, computerbased truck dispatching systems have been widely used for this purpose. Existing approaches
can be classified into: rule-driven heuristics, constrained-assignment approaches, and plandriven approaches (Munirathinam and Yingling 1994).
Existing commercial solutions in the mining industry are commonly plan-driven systems,
operating by making real-time truck assignments while maintaining conformance to an established haulage allocation plan. These systems consist of two components: the haulage allocation
component and the dispatching component (Munirathinam and Yingling 1994). The haulage
allocation component designs an allocation plan as a set of material flow rates from diggers to
process plants and stockpiles, e.g., kilograms per second of material from a particular digger
to specific dumps (i.e., plants and stockpiles). Such plans are designed in a way that the production targets of the company for a certain time horizon (e.g., a 12-hour shift or 24 hours)
are fulfilled subject to the operational constraints. Given that the mineral deposit is broken
into smaller segments, or blocks, the company’s targets are often the amount of material that
must be extracted from certain blocks and sent to certain dumps. The dispatching component
attempts to achieve the allocation plan through assigning individual haul trucks to haul routes.
This paper focuses on the haulage allocation component. A variety of methods have been
developed to generate optimal flow rates, often comprising a linear programming model. However, a significant limitation of these methods is that they optimise flow rates only for instantaneous production, and do not have an awareness of the production target for the entire
time horizon. They are also unable to plan around upcoming disruptions, such as planned
maintenance and breaks, or changes in equipment availability (e.g., changes in the number of