Dynamic Simultaneous Optimization of Mineral Value Chains Under Resource Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Dynamic Simultaneous Optimization of Mineral Value Chains Under Resource Uncertainty write by Maria Del Castillo Suarez. This book was released on 2018. Dynamic Simultaneous Optimization of Mineral Value Chains Under Resource Uncertainty available in PDF, EPUB and Kindle. "Mining complexes are mineral value chains where extracted material from different mines is transformed into sellable products through a set of processing streams. This value chain is governed by uncertainties at different levels, from the geological attributes of the orebody at the mine(s), to the different operational and processing components that lead the sellable products to the market. Stochastic simultaneous optimization formulations for industrial mining complexes have proven to be effective in generating reliable strategic plans that maximize net present value and, at the same time, manage and reduce risk. However, because of the uncertainties governing a mining complex, particularly the ones related to the geological attributes which define the supply of the system, it has become a priority to integrate flexibility mechanisms that allow a mining project to change and adapt as more information becomes available. Within this adaptability, optimizing the investment timing of high-magnitude capital expenditures throughout the life-of-mine is a priority, due to their high impact on the annual cash-flows and on their effects over the physical mining schedule. Additionally, to improve a mining complex's ability to meet production targets and overall performance, advanced mechanisms should be developed to ensure complex blending constraints are met, managing the geometallurgical variables of the deposit.This thesis presents a methodology to embed flexibility into mineral value chains, by allowing the strategic mine plan of a mining complex to dynamically consider possible options and alternatives for reacting and adapting to future changes. For this, first, a study on extraction capacity optimization is presented, followed by the development of a mechanism to deal with complex variables of the deposit to meet blending constraints and production targets. These two components are later integrated into a dynamic optimization model, which optimizes the mining complex's mine plan under geological uncertainty, integrating flexible investment alternatives, as well as operational modes.The dynamic model developed produces a unique initial extraction sequence, while keeping a viable flexible long-term plan for future investment decisions, as may be needed. The flexible long-term plan is obtained through a dynamic optimization which allows making transitioning plans upfront to facilitate change. This method introduces a new adapted multistage stochastic programming model which expands upon the two-stage framework by performing multiple recourse stages that are solved iteratively, allowing parallel designs to be generated in a scenario-tree structure. In this model, dynamic decisions over capital expenditures are made sequentially over time, based on information that becomes available over production time. The above model is subsequently extended to include alternatives over operating modes at different levels of the mineral value chain. More specifically, optimal operating modes are chosen per period, selecting blasting patterns at the mine, and processing relations of throughput and recovery at the plant. The practical implications of the proposed method are demonstrated through an application over a copper-gold mining complex, where the dynamic model presents a 10.5% increase in net present value compared to a traditional two-stage stochastic formulation.The dynamic mining complex formulation proposed is able to include flexibility into the optimization of the strategic plan of a mineral value chain. This enables possible developments within the feasible set of alternatives that can be taken, considering the mining complex's configuration, capacities, and constraints. The proposed model is able to generate feasible, operational schedules, while providing a wider view of the mining complex's performance, easing the transition to possible changes due to the periodic unveiling of uncertainty." --
Mineral Supply Chain Optimization Under Uncertainty Using Approximate Dynamic Programming
Mineral Supply Chain Optimization Under Uncertainty Using Approximate Dynamic Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mineral Supply Chain Optimization Under Uncertainty Using Approximate Dynamic Programming write by Cosmin Paduraru. This book was released on 2015. Mineral Supply Chain Optimization Under Uncertainty Using Approximate Dynamic Programming available in PDF, EPUB and Kindle.
Optimizing Mineral Value Chain with Market Uncertainty Using Benders Decomposition
Optimizing Mineral Value Chain with Market Uncertainty Using Benders Decomposition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimizing Mineral Value Chain with Market Uncertainty Using Benders Decomposition write by Jian (Ray) Zhang. This book was released on 2020. Optimizing Mineral Value Chain with Market Uncertainty Using Benders Decomposition available in PDF, EPUB and Kindle. A Benders decomposition-based method is developed to simultaneously optimize the upstream and the downstream of a mineral value chain. Mining blocks representing mineral deposits are dynamically aggregated based on the dual solution of the sub-problem to reduce the complexity in the upstream mine production scheduling. The production schedule obtained based on the aggregated scheduling units is then improved through a moving-window amelioration method. By observing the results of a series of numerical tests, we show that the proposed method effectively optimizes a mineral value chain by synchronizing the upstream mine production scheduling and the downstream material flow and process planning. The results of the numerical tests also show that ignoring the market uncertainty can result in the underestimation of profitability because of the underestimated value of low-grade materials. In order to adapt to the existence of market uncertainty, the stochastic optimizer suggests a higher processing capacity investment in the processing plant and a different long-term mine production schedule.
Stochastic Mining Supply Chain Optimization
Stochastic Mining Supply Chain Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Mining Supply Chain Optimization write by Iain Farmer. This book was released on 2017. Stochastic Mining Supply Chain Optimization available in PDF, EPUB and Kindle. "The mining value chain comprises many inter-related components. When the individual components are optimized separately the value that can be generated from the enterprise suffers. Global optimization of the mining value chain requires a shift away from conventional methods of optimization and towards the simultaneous optimization of all related aspects, including: the mine's extraction sequence, material destination decisions, material transport decisions, and equipment capacities. Further, if these decisions are to be robust, they must be made while considering sources of uncertainty. The contributions included in this thesis are meant to help industry practitioners plan and evaluate mining projects under uncertainty. Specifically, the simultaneous integration of capacity decisions in long-term scheduling is meant to provide a tool that generates a NPV-optimal mine sequence and destination policy that is also synchronized with equipment capacities selected while being robust to two sources of uncertainty. Further, a schedule-based method of pushback design is developed in an effort to construct pushbacks from an optimal mine sequence. The method is applied in order to preserve as much of the sequence's optimality as possible while generating an operational mine plan." --
An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation
An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation write by Mélanie LaRoche-Boisvert. This book was released on 2021. An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation available in PDF, EPUB and Kindle. "A mineral value chain or mining complex is an integrated system representing all components of a mining operation for the extraction, transportation and transformation of material, from sources (open pit and underground mines) to customers or the spot market. Simultaneous stochastic optimization aims to optimize all components of a mineral value chain, including extraction schedules for the mines, stockpile management, processing and transportation scheduling, jointly to capitalize on the synergies that exist within the system. Additionally, the simultaneous stochastic optimization approach incorporates material supply or geological uncertainty using equally probable geostatistical (stochastic) simulations of the attributes of interest of the deposits. The incorporation of material supply uncertainty allows the approach to manage the related major technical risks.The first contribution of this thesis is the application of simultaneous stochastic optimization at a three-mine open pit gold mining complex, incorporating material supply uncertainty using stochastic simulations of the gold grades of each deposit. The case study maximizes the net present value of the operation by generating life-of-mine schedules for each deposit considered and stockpile management plans, which maximize gold production and minimize the associated costs. The study also assesses the impacts of material hardness on the processing facilities, notably the SAG mill, and the recovered gold. This assessment indicates that the SAG mill is the bottleneck of the operation; due to the lack of availability of soft material in the considered deposits, the throughput of material at the SAG mill is significantly lowered. The second contribution of this thesis is a new stochastic mathematical programming formulation jointly optimizing long-term extraction scheduling and mine-to-port transportation scheduling for mining complexes under supply uncertainty. Mine-to-port transportation systems represent an important component of certain mining complexes, such as iron ore mining complexes, ensuring that extracted products reach their intended clients. This component of the mineral value chain has not been included in previous simultaneous stochastic optimization formulations, ignoring the interactions between the transportation system and the other components of the mining complex. The proposed model simultaneously optimizes extraction scheduling, stockpile management, mine-to-port transportation scheduling and blending under material supply uncertainty. It aims to minimize the costs associated with meeting quantity and quality demand for the products at the port, managing the risks associated with the material supply uncertainty using stochastic simulations of grades. The model is applied to an iron ore mining complex consisting of two open pit mines, each with a waste dump, a stockpile and a loading area, connected to a single port by a railway system. Material is transported by two trains. At the port, demand for two products are considered, each with quality constraints relating to five elements. Stochastic simulations of the five elements considered are used to represent the material supply uncertainty. By optimizing the extraction and the mine-to-port transportation jointly, the case study is able to determine that only the first train is necessary to transport material to meet demand at the port for the first three years of mine life; for the remainder, the second train is also needed. As such, the second train could be allocated to another operation for better use during the first three years of operation or its purchase could be delayed. The model provides decision makers with a realistic use of the mine-to-port transportation system"--
