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Abstract
Discussion Forum (0)
The process of strategic underground mining production planning is an optimization decision-making process which entails a mining sequence that takes into consideration the physical limitations, resource and production constraints, and financial performance of the mine. An optimal mine life is detailed in proper scheduling of all available resources and more importantly the mining and development sequence. The complexities and computational difficulties associated with underground mine planning makes it challenging and open to further research. The application of mathematical programming models generates optimal and robust strategic underground production schedules. However, current mathematical programming models lack the ability to produce practical underground mine plans since they are not able to deal with: i) exhaustive development layout functionalities ii) comprehensive operational parameters, and iii) realistic mining problem sizes. This research presents a robust mathematical programming framework based on Mixed Integer Linear Programming (MILP) formulation for open stope underground mining. The MILP model maximizes the Net Present Value (NPV) of the mining project and determines the capital, ventilation, operational development schedules in addition to the mining/processing schedule. The model further incorporates backfilling. The model is implemented for a cobalt deposit case study to investigate the resource extraction strategy that maximizes NPV and generates a practical mine plan
The process of strategic underground mining production planning is an optimization decision-making process which entails a mining sequence that takes into consideration the physical limitations, resource and production constraints, and financial performance of the mine. An optimal mine life is detailed in proper scheduling of all available resources and more importantly the mining and development sequence. The complexities and computational difficulties associated with underground mine planning makes it challenging and open to further research. The application of mathematical programming models generates optimal and robust strategic underground production schedules. However, current mathematical programming models lack the ability to produce practical underground mine plans since they are not able to deal with: i) exhaustive development layout functionalities ii) comprehensive operational parameters, and iii) realistic mining problem sizes. This research presents a robust mathematical programming framework based on Mixed Integer Linear Programming (MILP) formulation for open stope underground mining. The MILP model maximizes the Net Present Value (NPV) of the mining project and determines the capital, ventilation, operational development schedules in addition to the mining/processing schedule. The model further incorporates backfilling. The model is implemented for a cobalt deposit case study to investigate the resource extraction strategy that maximizes NPV and generates a practical mine plan
A Robust Mathematical Programming Framework for Underground Open Stope Mining Production Planning Optimization
Disclosure(s): n/a
Emmanuel Appianing
Abstract
Discussion Forum (0)
The process of strategic underground mining production planning is an optimization decision-making process which entails a mining sequence that takes into consideration the physical limitations, resource and production constraints, and financial performance of the mine. An optimal mine life is detailed in proper scheduling of all available resources and more importantly the mining and development sequence. The complexities and computational difficulties associated with underground mine planning makes it challenging and open to further research. The application of mathematical programming models generates optimal and robust strategic underground production schedules. However, current mathematical programming models lack the ability to produce practical underground mine plans since they are not able to deal with: i) exhaustive development layout functionalities ii) comprehensive operational parameters, and iii) realistic mining problem sizes. This research presents a robust mathematical programming framework based on Mixed Integer Linear Programming (MILP) formulation for open stope underground mining. The MILP model maximizes the Net Present Value (NPV) of the mining project and determines the capital, ventilation, operational development schedules in addition to the mining/processing schedule. The model further incorporates backfilling. The model is implemented for a cobalt deposit case study to investigate the resource extraction strategy that maximizes NPV and generates a practical mine plan
The process of strategic underground mining production planning is an optimization decision-making process which entails a mining sequence that takes into consideration the physical limitations, resource and production constraints, and financial performance of the mine. An optimal mine life is detailed in proper scheduling of all available resources and more importantly the mining and development sequence. The complexities and computational difficulties associated with underground mine planning makes it challenging and open to further research. The application of mathematical programming models generates optimal and robust strategic underground production schedules. However, current mathematical programming models lack the ability to produce practical underground mine plans since they are not able to deal with: i) exhaustive development layout functionalities ii) comprehensive operational parameters, and iii) realistic mining problem sizes. This research presents a robust mathematical programming framework based on Mixed Integer Linear Programming (MILP) formulation for open stope underground mining. The MILP model maximizes the Net Present Value (NPV) of the mining project and determines the capital, ventilation, operational development schedules in addition to the mining/processing schedule. The model further incorporates backfilling. The model is implemented for a cobalt deposit case study to investigate the resource extraction strategy that maximizes NPV and generates a practical mine plan
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