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Evaluation of mineral reserves: A simulation approach [M]. Journal of Central South University, , 21 8 : — Evaluation of the effect of geometrical parameters on stope probability of failure in the open stoping method using numerical modeling [J]. Correspondence to Mustafa Kumral. Designing an optimal stope layout for underground mining based on a heuristic algorithm [J]. Journal of Mining Science, , 49 1 : 68— Stochastic short-term mine production schedule accounting for fleet allocation, operational considerations and blending restrictions [J]. Journal of Mining Science, , 47 2 : — Stochastic long-term production scheduling of iron ore deposits: Integrating joint multi-element geological uncertainty [J]. Rent this article via DeepDyve. Stochastic integer programming for optimising long term production schedules of open pit mines: methods, application and value of stochastic solutions [J]. European Journal of Operational Research, , 3 : — Simulated learning model for mineable reserves evaluation in surface mining projects [J]. South Univ. Mining Technology, , 4 : — Stochastic optimization for strategic mine planning: A decade of developments [J]. Natural Resources Research, , 28 2 : — Download references. Villalba Matamoros, M. Massachusetts Institute of Technology, Genetic algorithms in search, optimization, and machine learning [M]. SME Transactions, , 67— Google Scholar. Academic Press, New York: Oxford University Press, Conditional simulation algorithms for modelling orebody uncertainty in open pit optimisation [J]. Martha E. Applied Soft Computing, , — Heuristic stope layout optimization accounting for variable stope dimensions and dilution management [J]. Journal of Central South University of Technology, , 17 3 : — Evaluation of the impact of commodity price change on mine plan of underground mining [J]. A value adding approach to hard-rock underground mining operations: Balancing orebody orientation and mining direction through meta-heuristic optimization. New York: Addison Wesley Longman, Practical rock engineering in the optimization of stope dimensions-application and cost-effectiveness [J]. This process is called stope layout optimization SLO and implemented under site-specific geotechnical, operational and economic constraints. Optimizing stope designs and sequences in underground mines [J]. Mining Technology, , 2 : 49— Underground mine planning: Stope layout optimization under uncertainty using genetic algorithms [J]. International Journal of Mining, Reclamation and Environment , 33 5 : — Expert Systems with Applications, , 37 2 : — Cost optimisation for underground mining networks [J]. This paper proposes an approach whereby paths in the SLO are defined as decision variables to avoid the cost of mining in the wrong direction. Optimization and Engineering, , 6 2 : — Mining geostatistics [M]. SME Transactions, , — Australaisian code for reporting of exploration results, mineral resources and ore reserves [M]. International Journal of Mining Science and Technology, , 29 3 : — Dynamic optimization of cutoff grade in underground metal mining [J]. Reprints and Permissions. International Journal of Mining, Reclamation and Environment, , 31 6 : — Montreal, — Workshop on Local Search for Planning and Scheduling. Mining Technology, , 2 : — A critical survey of the existing stope layout optimization techniques [J]. View author publications. In an underground mine based on stoping method, orebody part s maximizing profit should be determined. Managing grade risk in stope design optimisation: probabilistic mathematical programming model and application in sublevel stoping [J]. A new algorithm for stope boundary optimization [J]. CIM Bulletin, , 82 : 63— Orthogonal design and numerical simulation of room and pillar configurations in fractured stopes [J]. Journal of Mining Science, , 41 5 : — A heuristic approach to optimal design of an underground mine stope layout [J]. Pearson Education, Inc. About this article. For practical purpose, the design obtained by SLO shows consecutive stopes in one path, which assists in defining the mining direction of these stopes. Download citation. An introduction to genetic algorithms [M]. However, this direction may not accommodate the spatial distribution of the ore grade: if the orebody orientation and mining direction differ, the value of the mining operation may decrease. International Journal of Mining Science and Technology, , 25 3 : — New York: Kluwer Academic, 55— Calibration of genetic algorithm parameters for mining-related optimization problems [J]. Received : 17 August Accepted : 20 July Published : 03 January Issue Date : November Search SpringerLink Search. Springer, 1— Optimisation of stope limits using a heuristic approach [J]. Villalba Matamoros View author publications. Rights and permissions Reprints and Permissions. Abstract Underground mines require complex construction activities including the shaft, levels, raises, winzes and ore passes. International Journal of Mining and Mineral Engineering, , 8 1 : 1— Artificial intelligence: A modern approach [M].

Underground mines require complex construction activities including the shaft, levels, raises, winzes and ore passes. Cite this article Villalba Matamoros, M.

Geostatistical reservoir modeling [M]. This is a preview of subscription content, log in to check access. Melbourne, — A 3D approximate hybrid algorithm for stope boundary optimization [J]. International Journal of Mining Science and Technology, , 25 5 : — Implementation and comparison of four stope boundary optimization algorithms in an existing underground mine [J].