There are multiple stages in a mining operation in which a mining engineer must draw polygons to be used as operation guidelines. These polygons are drawn by hand and based on the engineer’s experienc

This paper deals with optimal decisions regarding truck and shovel scheduling problem in open-pit mines. A mixed-integer linear goal programming model (MILGP) is formulated for solving the problem, aiming at four major goals: (1) maximise production, (b) minimise deviations in head grade, (c) minimise deviations in tonnage to the ore destinations, and (d) minimise fuel consumption of mining trucks. This paper also examines the extent to which the priority of objectives can affect the results and efficiency of the mining operation. Implementation of the model with a copper mine case study demonstrated that the proposed model is effective and efficient.

This work deals with the optimal decisions for materials handling in open-pit mines. The main purpose of this research is to present a multi-stage approach, which has three sequential stages: (a) fleet size selection stage, (b) fleet allocation stage, and (c) real-time truck dispatching stage. At first, a simulation-based optimisation method is provided to evaluate the optimal number of trucks. Then, a new heuristic algorithm is developed for making operational decisions. To evaluate the performance of the proposed framework, the dispatching algorithm used by Modular Mining DISPATCH is developed. The results indicate that the proposed method yields fairly good performance.

The decision to exploit a mineral deposit that can be extracted by open pit and/or underground mining involves consideration of the following options: (a) independent open pit extraction; (b) independent underground extraction; (c) simultaneous open pit and underground (OPUG) extraction; (d) sequential OPUG extraction; and (e) combinations of (c) and (d). This paper investigates the extraction strategy for deposits using Mixed Integer Linear Programming (MILP) optimisation framework to maximise the net present value and determine the schedules for mining, processing, underground capital and operational developments, and 3D crown pillar position. The MILP framework is implemented for a gold deposit. The results showed a combined sequential and simultaneous open pit and underground (OPUG) mining with crown pillar as the optimal extraction option generating NPV that is 11% and 13% better than independent OP or UG mining, respectively.

Strategic mine planning and waste management are an important aspect of surface mining operations. Recent environmental and regulatory requirements make waste management an integral part of mine planning in the oil sands industry. The research problem here is determining the order of extraction of ore, dyke material and waste to be removed from a predefined ultimate pit limit over the mine life that maximises the net present value of the operation. We have developed, implemented, and tested a proposed mixed integer goal programming theoretical framework for oil sands open pit production scheduling with multiple material types. The formulation uses binary integer variables to control mining precedence and continuous variables to control mining of ore and dyke material. There are also goal deviational variables and penalty costs and priorities that must be set up by the planner. The optimisation model was implemented in TOMLAB/CPLEX environment. The developed model proved to be able to generate a uniform schedule for ore and dyke material. This is in line with recent regulatory requirements by Alberta Energy Resources and Conservation Board (Directive 074) which requires oil sands mining companies to develop life of mine plans which ties in to their in-pit tailings disposal strategy. It also provides a practical mining sequence that is consistent with mining oil sands deposit. Similarly, tradeoffs between achieving a goal and maximising NPV can be made.