Optimized depth of transition from Open Pit to underground coal mining

A Review of Models and Algorithms for Surface-Underground Mining Options and Transitions Optimization: Some Lessons Learnt and the Way Forward

“…The indicators can be broadly grouped into geologic, operational, geotechnical, economic, and mine management strategy on global business economic outlook [7,61]. These transition indicators are key to the identification and development of the set of constraints required for optimizing the OP-UG mining options and transitions planning problem [4,9,25].…”

“…The positioning of the required crown pillar in the surface-underground mining options and transitions planning problem is key to the operations of such mines. Some researchers pre-selected the depth of the crown pillar (transition depth) before evaluating portions above the crown pillar for OP mining and portions below the crown pillar for underground mining [4,18,25,27,28]. This may lead to suboptimal solutions and will require evaluating multiple crown pillar locations in a scenario-based approach.…”

“…Some of the models and algorithms are Lerchs-Grossman algorithm, Seymour algorithm, floating cone technique, dynamic programming, neural network, theory of graphs, and network flow algorithm. These models and algorithms are used in software packages including NPV Scheduler, Whittle Four-X, MineSched, Vulcan, MineScape, and MineSight [25,26].…”

“…Existing optimization algorithms used in attempting the mining options problem include the Lerchs-Grossman (LG) algorithm, Seymour algorithm, floating cone technique, network flows, dynamic programming, neural network, theory of graphs, and mathematical formulations [25]. Some authors have studied the surface-underground mining options and transitions optimization problem with available commercial software packages including Surpac Vision, Datamine's NPV Scheduler, Whittle Four-X, Geovia MineSched, integrated 3D CAD systems of Datamine, Vulcan, MineScape, MineSight, Isatis, XPAC, Mineable Reserve Optimizer (MRO), Blasor pit optimization tool, COMET cut-off grade and schedule optimizer, and Datamine Studio 3 [7,9,17,26,27].…”

“…Although Bakhtavar, Shahriar, and Oraee [3] employed a heuristic algorithm to compare economic block values computed for both open pit and underground mining on a depth flow basis to solve the SUMOTO problem, results from the heuristic algorithm do not offer a measure of optimality as it is the case in mathematical programming optimization. Notable authors that used mathematical programming to solve the mining transition problem limit their model to the determination of transition depth and block extraction sequence for the open pit and underground mining operations [2,4,8,9,[11][12][13][14][15][17][18][19]24,25,28,29]. Similarly, other authors have developed stochastic mathematical programming models to solve the surface-underground mining options and transitions optimization problem.…”