Applications of simulation and optimization techniques in optimizing room and pillar mining systems

The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) test the hypothesis that heuristic pre-processing can be used to increase the computational efficiency of branch and cut solutions to the BILP problem of R&P mine sequencing. A DES model of an existing R&P mine was built, that is capable of evaluating the effect of variable panel width on the unit cost and productivity of the mining system. For the system and operating conditions evaluated, the result showed that a 17-entry panel is optimal. The result also showed that, for the 17-entry panel studied, four shuttle cars per continuous miner is optimal for 80% of the defined mining segments with three shuttle cars optimal for the other 20%. The research successfully incorporated risk management into the R&P production sequencing problem, modeling the problem as BILP with block aggregation to minimize computational complexity. Three pre-processing algorithms based on generating problem-specific cutting planes were developed and used to investigate whether heuristic pre-processing can increase computational efficiency. Although, in some instances, the implemented pre-processing algorithms improved computational efficiency, the overall computational times were higher due to the high cost of generating the cutting planes --Abstract, page iii

Production Scheduling of an Open-pit Mining Complex with Waste Dump Constraints

The research work aims to solve the production scheduling problem for open pit mining complexes. It establishes a Mixed-Integer Programming (MIP) model that maximises the net present value of future cash flows and satisfies reserve, production capacity, mining block precedence, waste disposal, stockpiling, and pit sequence constraints. The model is validated and implemented with real-world case

Optimization of production planning in underground mining

Use of Integer programming (IP) or mixed integer programming (MIP) for formulation of mine optimization problem is best suited modelling approach for underground mining. Optimization algorithm for underground stope design problems cannot be generalised as geotechnical constraints for each method is different. This project concentrates on optimization model for open stoping mining method. The stope design model maximizes Net cash flow of the stope while adhering to the stope constraints. The methodology considers open stoping sequence, in which every block is moved towards the cross-cuts at the lower level. In this thesis, stopes are designed to maximize the undiscounted cash flow from the stope after satisfying stope height and extraction angle constraints. An integer programming formulation is developed and solved using CPLEX solver for single stope. The proposed algorithm is solved for first stope and then blocks for the crown pillar for first stope is identified. After eliminating the first stope and respective crown pillar data from the data set, algorithm is solved again for the second stope from the remaining data set. After stope design, production scheduling is done by applying heuristic approaches. Blocks from the stopes are extracted heuristically satisfying extracting angle, mining and processing constraints. Initially blocks from the first stope are selected and then to fulfil the constraints, some of the blocks from the second stope are selected. A study is carried out on the part of the Zinc mine data of India which contains 4992 number of blocks. Total 3 numbers of stopes are designed. The NPV of the considered data is found to be 7313.346 million rupees in 3 periods with total tonnage of 1.103 million tonnes. Metal content in 3 periods is found to be 86.485 thousand Tonnes. The overall dilution is found to be 3.82% with average dilution of 2.692

Оптимізація стійкості функціонування підсистем очисного вибою

Запропоновано новий підхід щодо оцінки стійкості функціонування виробничих підсистем в очисному вибої вугільних шахт. Для вирішення задачі застосовано комплексний підхід, який базується на впровадженні моделі стійкості виробничих зв’язків в очисному вибої, а також критеріїв прийняття рішень в умовах невизначеності для розробки рекомендацій щодо підвищення техніко-економічних показників. Встановлено, що стійкість функціонування підсистем в очисному вибої визначається співвідношенням потоків вхідних ресурсів у вигляді підготовленого фронту очисних робіт, засобів механізації, технологічних параметрів та вихідних – у вигляді кінцевого рівня продуктивності, собівартості видобутку та ін. Особливу увагу приділено розробці програмного забезпечення для впровадження описаних підходів у виробництво

Оптимизация устойчивости функционирования подсистем очистного забоя

Предложен новый подход к оценке устойчивости функционирования производственных подсистем в очистном забое угольных шахт. Для решения задачи применен комплексный подход, основанный на внедрении модели устойчивости производственных связей в очистном забое, а также критериев принятия решений в условиях неопределенности для разработки рекомендаций по повышению технико-экономических показателей. Установлено, что устойчивость функционирования подсистем в очистном забое определяется соотношением потоков входящих ресурсов в виде подготовленного фронта очистных работ, средств механизации, технологических параметров и выходных – в виде конечного уровня производительности, себестоимости добычи и др. Особое внимание уделено разработке программного обеспечения для внедрения описанных подходов в производство

Underground mine scheduling under uncertainty

17 USC 105 interim-entered record; under review.The article of record as published may be found at http://dx.doi.org/10.1016/j.ejor.2021.01.011Underground mine schedules seek to determine start dates for activities related to the extraction of ore, often with an objective of maximizing net present value; constraints enforce geotechnical precedence between activities, and restrict resource consumption on a per-time-period basis, e.g., development footage and extracted tons. Strategic schedules address these start dates at a coarse level, whereas tactical schedules must account for the day-to-day variability of underground mine operations, such as unanticipated equipment breakdowns and ground conditions, both of which might slow production. At the time of this writing, the underground mine scheduling literature is dominated by a deterministic treatment of the problem, usually modeled as a Resource Constrained Project Scheduling Problem (RCPSP), which precludes mine operators from reacting to unforeseen circumstances. Therefore, we propose a stochastic integer programming framework that: (i) characterizes uncertainty in duration and economic value for each underground mining activity; (ii) formulates a new stochastic variant of the RCPSP; (iii) suggests an optimization-based heuristic; and, (iv) produces implementable, tactical schedules in a practical amount of time and provides corresponding managerial insights.National Institute of Occupational Safety and HealthNational Agency for Research and Development (ANID

Economic efficiencies of the energy flows from the primary resource suppliers to the electric load centers

The economic efficiency of the electric energy system depends not only on the performance of the electric generation and transmission subsystems, but also on the ability to produce and transport the various forms of primary energy, particularly coal and natural gas. However, electric power systems have traditionally been developed and operated without a conscious awareness of the energy system-wide implications, namely the consideration of the integrated dynamics with the fuel markets and infrastructures. This has been partly due to the difficulty of formulating models capable of analyzing the large-scale, complex, time-dependent, and highly interconnected behavior of the integrated energy system. In this dissertation, a novel approach for studying the movements of coal, natural gas, and electricity in an integrated fashion is presented. Conceptually, the model developed is a simplified representation of the national infrastructures, structured as a generalized, multiperiod network composed of nodes and arcs. Under this formulation, fuel supply and electricity demand nodes are connected via a transportation network and the model is solved for the most efficient allocation of quantities and corresponding prices for the mutual benefits of all. The synergistic action of economic, physical, and environmental constraints produces the optimal pattern of energy flows. Key data elements are derived from various publicly available sources, including publications from the Energy Information Administration, survey forms administered by the Federal Energy Regulatory Commission, and databases maintained by the Environmental Protection Agency. The results of different test cases are analyzed to demonstrate that the decentralized level of decision-making combined with imperfect competition may be preventing the realization of potential cost savings. An overall optimization at the national level shows that there are opportunities to better utilize low cost generators, curtailing usage of higher cost units and increasing electric power trade, which would ultimately allow customers to benefit from lower electricity prices. In summary, the model developed is a simulation tool that helps build a better understanding of the complex dynamics and interdependencies of the coal, natural gas, and electricity networks. It enables public and private decision makers to carry out comprehensive analyses of a wide range of issues related to the energy sector, such as strategic planning, economic impact assessment, and the effects of different regulatory regimes