Download or read book Integrating Geometallurgical Ball Mill Throughput Predictions Into Short term Stochastic Production Scheduling in Mining Complexes written by Christian Both and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Simultaneous Short term Decision making in Mining Complexes Integrating Geometallurgy Assisted by Production Data written by Christian Both and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is an integrated business of mines and downstream facilities that extracts raw materials, converts extracted materials into sellable products, and transports products to markets and customers. Conventionally, individual components of a mining complex are optimized independently of each other, which causes underperformance of the mineral value chain. Simultaneous stochastic optimization of mining complexes has shown to create strategic mine plans that increase the net present value while reducing risk of meeting production targets by incorporating geological and price uncertainty. While these developments jointly optimize strategic decisions of a mining complex, short-term planning makes weekly to monthly decisions to best meet long-term production targets and maximize value. These decisions include short-term extraction sequence, destination of materials, and downstream material flow in mining complexes. Furthermore, the optimal allocation of the mining fleet is an important aspect of short-term planning; however, the joint stochastic optimization of short-term production schedules and fleet management in mining complexes has not yet been developed. Additionally, geometallurgical properties that drive revenues, costs, and the ability to meet production targets, are not integrated in the optimization of short-term production schedules in mining complexes. This thesis expands the simultaneous stochastic optimization of mining complexes for long-term planning into a decision-making framework for short-term mine planning through the incorporation of fleet management and geometallurgical prediction models of plant performances into the short-term optimization of mining complexes, which is assisted by the utilization of collected datasets from production processes in mines and processing plants. First, a new stochastic integer programming model for short-term planning is developed that extends the simultaneous stochastic optimization of mining complexes to allow the scheduling of a heterogeneous truck fleet and shovel allocations while considering the costs and loss of production caused by shovel relocation. Next to geological uncertainty, equipment performance uncertainties related to production rates, availabilities, and truck cycle times are integrated. Next, a geometallurgical model for the prediction of ball mill throughput in mining complexes is developed which utilizes drilling penetration rates and recorded throughput rates of the operating plant. The creation of hardness proportions avoids biases introduced by the change of support and blending of non-additive geometallurgical properties. By integrating the throughput prediction model into the simultaneous stochastic optimization formulation, planned production can be achieved reliably because scheduled materials match with the predicted mill performance. The throughput prediction model is extended thereafter by including recorded measurements of ball mill power draw and particle size distributions. Since the addition of new features increases the possibilities of non-linearities, a neural network is used. The prediction of metallurgical responses of the operating plant and their incorporation into short-term stochastic production scheduling is finally extended by creating prediction models of consumption rates of reagents and consumables in a gold mining complex. With the new developments presented in this thesis, the simultaneous stochastic optimization of mining complexes can now be applied for short-term planning, modelling the operational aspects of the mining fleet and metallurgical behaviour of processing plants in greater detail. The integration of these short-term aspects leads to short-term mine plans that are more likely to align with long-term production targets while benefitting from synergistic effects that maximize the profit of the mineral value chain"--

Download or read book The Stochastic Optimization of Long and Short term Mine Production Schedules Incorporating Uncertainty in Geology and Equipment Performance written by Matthew Quigley and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mine production scheduling consists of defining the extraction sequence and process allocation of mineralized material over some length of time. These decisions can be made at different time steps, which will entail varying objectives subject to different technical and operational constraints. Long-term mine production scheduling usually takes place at an annual scale for the entire life of mine and aims to maximize the net present value of the project while satisfying the mining and processing capacities. Short-term mine production scheduling consists of developing an extraction sequence on a shorter time scale, either months, weeks, or days. The goal is typically to maximize compliance with the production targets imposed by the long-term plan while considering more detailed operational constraints. Historically, these optimization frameworks have relied on the assumption of perfect knowledge of highly uncertain inputs. Developments in the field of stochastic mine planning have shown that incorporating uncertainty into the optimization of mine production schedules can add significant economic value while also minimizing the risk of deviating from production targets. This thesis will explore the benefits that stochastic mine planning can offer when applied to both long and short-term production scheduling problems.For the first exercise, the long-term mine production schedule of a rare earth element (REE) project is generated under geological uncertainty using a stochastic optimization framework. The uncertainty in REE grades is modelled using an efficient joint-simulation technique to preserve the strong cross-element relationships. The proposed approach avoids the use of the conventional total rare earth oxide grade. The stochastic long-term schedule is benchmarked against a deterministic schedule generated using an industry standard optimizer. The stochastic solution generates a 20% increase in expected NPV, ensures better utilization of the processing plant, and delivers a superior ore feed in terms of satisfying mineral and REE blending targets.For the second exercise, a formulation is proposed that simultaneously optimizes the short-term equipment plan and production schedule under both geological and equipment performance uncertainty. The proposed approach rectifies certain limitations of previous work in stochastic short-term planning by: incorporating a location-dependant shovel movement optimization; generating more realistic equipment performance scenarios; developing a new approach to facilitate more practical mine designs; and proposing model improvements to allow for a more efficient optimization of very large problem instances. The model is applied to a large copper mining complex and is compared to a more traditional approach, where the same formulation is implemented using averaged inputs for geology and equipment performance. The stochastic solution is more effective in mitigating the risk of deviating from tonnage targets at each processing destination, and the integration of equipment performance variability allows the stochastic optimizer to generate a block extraction sequence that is far more likely to be achieved." --

Download or read book Proceedings of the International Field Exploration and Development Conference 2023 written by Jia’en Lin and published by Springer Nature. This book was released on with total page 1347 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Ore Reserve Estimation and Strategic Mine Planning written by Roussos Dimitrakopoulos and published by Springer. This book was released on 2015-11-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mining business faces continual risks in producing metals and raw materials under fluctuating market demand. At the same time, the greatest uncertainty driving the risk and profitability of mining investments is the geological variability of mineral deposits. This supply uncertainty affects the prediction of economic value from the initial valuation of a mining project through mine planning, design and production scheduling. This book is the first of its kind, presenting state-of-the-art stochastic simulation and optimization techniques and step-by-step case studies. Quantification of geological uncertainty through new efficient conditional simulation techniques for large deposits, integration of uncertainty to stochastic optimization formulations for design and production scheduling and the concurrent management of risk are shown to create flexibility, options and oportunities, increase asset value, cashflows and return on investment. New approaches introduced include resource/reserve risk quantification, cost-effective drilling programs, pit design and long-term production scheduling optimization with simulated orebodies, ore reserve classification, geologic risk discounting, waste managing and demand driven scheduling, risk assessment in meeting project production schedules ahead of mining, risk based optimal stope design, options valuation when mining. Applications include commodities such as gold, copper, nickel, iron ore, coal and diamonds.

Download or read book Integrating Short term Stochastic Production Planning Updating to Mining Fleet Management in Industrial Mining Complexes written by Joao Pedro de Carvalho and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine to port Transportation written by Mélanie LaRoche-Boisvert and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Download or read book Stochastic Short term Production Scheduling and Shovel Allocation for Mining Complexes Including Stockpiling and Operational Alternatives written by Christian Both and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Simultaneous Stochastic Optimization written by Zachary Levinson and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is a fully integrated logistics network that represents the transportation and transformation of material from the source, open-pit and underground mines, to the customers and/or the spot market. Mining enterprises around the world aim to create a strategic mine plan for each of their assets that maximizes the value generated for a company and its stakeholders. Simultaneous stochastic optimization is used to generate a production schedule that defines the extraction sequence, stockpiling, processing, blending, capital investment and waste management decisions under supply uncertainty. The optimization approach exploits synergies within the mining complex by considering the contribution of each interconnected component in a single mathematical formulation. These components may include multiple mines, processors, stockpiles, waste facilities, and methods of transportation. In this thesis, a study of simultaneous stochastic optimization is completed in two operating gold mining complexes focusing primarily on the integration of waste management and capital investment decisions under supply uncertainty.The first application presents the simultaneous stochastic optimization of a gold mining complex focusing on waste management, particularly the uncertain aspects of acid generating waste. Typically, when optimizing the production schedule, the primary focus is to deliver valuable products to the market. However, this tends to ignore the environmental and economic impact of simplifying waste management requirements, including the storage and disposal of waste material. Stricter regulations and engineering requirements are transforming past mining practices to develop more sustainable operations. These transformations increase the financial cost of waste management and identify the requirement to integrate waste management into the production schedule. Additionally, misrepresenting the material uncertainty and variability associated with the amount of waste produced can impact, both, the stakeholders and the profitability of a mining complex. In this case study, a simultaneous stochastic optimization approach is applied to generate a long-term production schedule that considers waste management. The resulting schedule leads to a 6% increase in the net present value when compared to a conventional approach, while minimizing the likelihood of deviating from production targets and ensuring permit constraints are satisfied. Second, an innovative strategic mine planning approach is applied to a multi-mine and multi-process gold mining complex that simultaneously considers feasible capital investment alternatives and capacity management decisions that a mining enterprise may undertake. The simultaneous stochastic optimization framework determines the extraction sequence, stockpiling, processing stream, blending, waste management and capital investment decisions in a single mathematical model. A production schedule branches and adapts to uncertainty based on the likelihood of purchasing a feasible investment alternative that may increase mill throughput, acid consumption, and tailings capacity. Additionally, the mining rate is determined simultaneously by selecting the number of trucks and shovels required to maximize the value of the operation. The mining complex contains several sources – two open-pit gold mines and externally sourced ore material – stockpiles, waste dumps, tailings and three different processing streams. The simultaneous optimization framework integrates the blending of sulphates, carbonates, and organic carbon at the autoclave for refractory ore while managing acid consumption. The resulting production schedule indicates an increase in net present value as the optimization model adapts to uncertainty and manages the technical risk of capital investment decisions"--

Download or read book Stochastic Optimization of Stope Design and Long term Underground Mining Production Scheduling for Sublevel Open Stoping Mining Operations written by Matheus Furtado E. Faria and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Underground mine planning defines the design of technically producible economic material volumes and development openings, the sequence of multiple underground activities, and the material destinations within a mineral deposit throughout the mine's life, aiming to maximize the net present value (NPV). Due to the existence of different mining methods and the inherent operational and computational complexities, this planning is commonly performed through a stepwise optimization process in which the stope layout is preliminarily designed. Subsequently, the network of developments interconnecting the production areas is conceived, defining the precedence of underground mining activities. Finally, the strategic underground mine production scheduling is optimized, the only step that accounts for the time value of money. Available optimization methods have been focused separately on each of the planning steps, which do not benefit from the synergies between the planning steps. Additionally, most of the previously mentioned methods are deterministic; that is, they neglect many sources of uncertainty, which has been extensively demonstrated to have a significant impact on the profitability and feasibility of mining operations. Therefore, this thesis proposes stochastic optimization methods for underground mines by employing a sublevel open stoping mining method and ultimately attempts to integrate the mine design and production scheduling into a single optimization framework. The first part of this thesis presents a stochastic optimization method of stope design along with the commonly used sequential underground mine planning framework. A set of geostatistical simulations is used to quantify the variability and uncertainty of grades within the mineral deposit. The proposed method aims to maximize the undiscounted profit while capitalizing on the upside potential in terms of recoverable metal of the generated stope layout. It also accounts for the development costs of potential production levels and stopes. The application of this stochastic approach at an underground gold mine achieved a 40% higher undiscounted profit and 21% recoverable metal when benchmarked against an industry-standard deterministic stope design software tool. The second part of this thesis presents an integrated stochastic optimization of stope design and long-term underground mine production scheduling by integrating time-dependent development costs and production targets. The mathematical model seeks to maximize the NPV from the scheduled stopes, as well as to minimize the shaft, drifts and crosscuts development costs and maintenance costs to keep the levels in operation while managing the risk of failing to meet yearly productions targets. Therefore, an optimal underground mine design is yielded as an output from the optimized production schedule. The method also opens new avenues to account for time-dependent sources of uncertainty that cannot be incorporated into the stope design optimization in the sequential underground mine planning framework. A case study at an underground gold mine demonstrates that the proposed method generates more selective stopes and physically different production levels, which correspond to an 11% higher NPV and a shorter life-of-mine by two years, as compared to the sequential optimization framework"--

Download or read book Applications of Tabu Search Parallel Metaheuristic for Stochastic Long term Production Scheduling written by Renaud Senecal and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In open pit mine planning, the mine deposit is discretized into mining blocks, where the size of these mining blocks is defined by the mine's extracting equipment capacity and selectivity. Mining blocks are removed from the ground at different periods and sent to various destinations to be processed, stockpiled or dumped. Long-term production scheduling with multiple destinations is used in the mining industry, to provide guidelines for this extraction process, deciding the mining period and the destination policy that should apply for each mining block. The destination policy aims to optimize where to send the extracted material, in order to maximize the discounted cash flow according to the system capacity. Stochastic long-term production scheduling with multiple destinations includes the uncertainty associated with the grade's material in the optimization process, by maximizing the net present value, while reducing the risk of not meeting the different production targets at each destination. For deposits represented by a large number of mining blocks, the optimization leads to very complex and large mathematical programs, this cannot be solved to optimality using exact methods such as Branch and Bound. In this thesis, stochastic integer programming formulations are used to integrate the uncertainty directly into the optimization of the long-term production scheduling problem, and Parallel Tabu Search metaheuristics are presented as an approach to provide nearby optimal solution, in a reasonable amount of time. Two different approaches are presented here for the destination policy during the optimization process, based on the economic value of each block. The first approach uses a fixed destination policy, which sends each block to its more profitable destination before the optimization, whereas the second one considers optimizing the policy simultaneously within the optimization process of a life-of-mine schedule.The first part of this thesis, Chapter 3, presents three different implementations of parallel Tabu Search metaheuristics to solve a previously existing stochastic integer program, designed to provide optimal solution for the life-of-mine production schedule with multiples destinations, under geological uncertainty and under a fix destination policy. The first two methods allow a more extensive search of the solution space, the first using several independent Tabu Searches, whereas the second allows communication between the different Tabu Searches to broadcast information. The third method aims to provide a more intensive search by exploring different local area simultaneously, starting from a single solution. An application to a deposit of about 70,000 mining blocks is shown to assess the ability of all methods to generate a schedule with minimized deviations in practical amount of time.In the second part, Chapter 4, a stochastic integer program that jointly optimizes the destination and the year of extraction for each mining block is presented. A parallel multi-neighbourhood Tabu Search implementation is used to approximate the optimal solution of this formulation. The approach considers optimizing simultaneously both the destination and the period of extraction of each mining block by defining different types of neighbour solutions to explore. The computational complexity added by considering simultaneously extraction and destination variables is reduced by the use of a load balancing strategy to distribute the work equally among the different processors. An application at a deposit of about 100,000 mining blocks is made to show the ability of the method to generate a schedule where the production targets are met and the NPV is maximized in a practical amount of time." --

Download or read book Stochastic Short term Production Scheduling Accounting for Fleet Allocation Operational Considerations Blending Restrictions and Future Multi element Ore Control Data written by Martha Villalba Matamoros and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mine production scheduling may be long-term or short-term based on the time period considered and the final objective. The optimization goal of short-term production scheduling is to minimize the mining cost expected from a mine while satisfying operational constraints, such as mining slope, grade blending, metal production, mining capacity and processing capacity; however some parameters may be uncertain, such as metal quality and fleet parameters. Traditional short-term production planning is carried out by two sequential optimizations, production schedule is defined at the first step and the available fleet is evaluated for this schedule as a second step, however; the fleet availability, hauling time and mining considerations do not influence the schedule decision. In addition, the fleet optimization algorithms do not consider uncertainty in their parameters and do not take into account the local mineralization of the deposit because a single possibly misleading total aggregated block tonnage is linked to each sector to be mined. The local mineralization or local scale variability between blocks assists in the blending process and metal quality control; however, the traditional short-term production scheduling is based on exploration drilling or a sparse data ore body model, while in practice grade control data or close spacing blasthole drilling classify the material as ore and waste because their short-scale information is not available at the time of the monthly short-term planning. The local variability is relevant in the short-term production scheduling to define the destination of the material.The short-term mine production scheduling in this thesis is developed as a single formulation where mining considerations, production constraints, uncertainty in the orebody metal quantity, as well as fleet parameters, are evaluated together to define a well informed sequence of mining that results in high performance at the mine operation. The formulation is implemented at a multi-element iron mine and the resulting monthly schedules show lower cost, minable patterns and, efficient fleet allocation, that ensures a higher and less variable utilization of the fleet over the conventional schedule approach.Uninformed and ultimately costly decisions can be taken because of imperfect geological knowledge or information effect. The orebody uncertainty may be updated by simulated future ore control data to account for local scale grade variability, and the information used to discriminate ore and waste in practice. Multi-element orebody uncertainty models are updated based on the correlation of exploration data and past ore control data, this orebody uncertainty is then used to optimize the short-term production scheduling that leads to better performance in terms of matching ore quality targets and delivering recoverable reserves." --

Download or read book Integer Programming to Evaluate Operational Impact of Penetration Rate Predictive Model written by Sebastian Arenas Bermúdez and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Short-term mine production scheduling for underground mines is considered to be both complex and crucial not only for having successful operations but also for accomplishing targets stated for the medium- and long-term mine plans. Moreover, underground operations are also known for having a significant amount of independent decisions concerning the available resources, tasks to be accomplished, and technical aspects of the underground mining openings. Consequently, for having high productivity within the operations, it is necessary to utilize a decision-making tool to build short-term production plans. Furthermore, incorporating predictions of performances based on historical operational data into the decision-making tool allows the decision-makers to accumulate more knowledge about the reality of the operation. This thesis explores the benefits that performance predictions can offer when incorporating them into the generation of drilling plans within the context of underground mines. In particular, an artificial neural network (ANN) is trained with operational data from an underground gold mine. Consequently, the trained network is used to predict the rate of penetration (ROP) for all possible combinations between the available drilling machines and operators, activities to be performed, and openings or destinations where these tasks can be executed. Moreover, an integer program formulation is constructed to demonstrate the impact of incorporating these predictions into operational decision-making. The integer programming formulation aims to maximize the drilled meters per day while respecting physical and operational constraints. A comparison between the initial drilling plan of operations and the plans given by the optimization model with and without accounting for the predictions is performed. The plan generated by the model which utilizes the predictions resulting from the neural network outperforms both the initial plan of drilling activities and the plan generated by the optimization model without accounting for the predictions during the first 15 days of operations"--

Download or read book Simultaneous Stochastic Optimization of Production Scheduling at Twin Creeks Mining Complex Nevada written by Luis Montiel and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis of a Mine mill Production System Using Simulation and Integer Programming written by Jun Zhou and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modelling Geological Uncertainty for Stochastic Short term Production Scheduling in Open Pit Metal Mines written by Arja Jogita Jewbali and published by . This book was released on 2006 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Unifed Modelling and Simultaneous Optimization of Open Pit Mining Complexes with Supply Uncertainty written by Ryan Goodfellow and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is an integrated business that extracts materials from open pit or underground mines, treats extracted materials via a series of processing facilities that are interconnected by various material handling methods, and generates a set of products that are sold and delivered to customers and/or the spot market. The primary objective when optimizing a mining complex is to maximize its value for the business and its stakeholders while obeying the technical constraints that limit production. This optimization is traditionally performed by treating the various components independently, leading to the suboptimal use of the natural resources and financial capital, and the underperformance of the mining complex. The global optimization of mining complexes aims to simultaneously optimize the mine production schedules, which define the distribution of materials over time, the destination policies, which define where extracted materials are sent, and the use of the various processing streams for processing, distribution and product marketing. As the size of the mining complex grows, there is a compounded effect that uncertainty has on the components, and new stochastic optimization methods are needed to manage this risk. This thesis aims to generate a unified modelling and global optimization methodology that integrates supply uncertainty and manages risk in the design and operation of mining complexes, and can be adapted to suit the needs and objectives of individual operations.This work advances the related field of knowledge through the development of new models and methods for optimizing mining complexes with uncertainty, which is achieved through five major contributions. First, a stochastic global optimization method is developed to simultaneously optimize multi-mine production schedules, destination policies, processing streams and capital expenditures for capacity design; while existing state-of-the-art methods may address some of these aspects, they have not been previously integrated in a simultaneous optimization model that does not rely on divvying up the global model into sub-problems. Second, a new, unified modelling approach is developed that permits the proposed methods to be tested on many different types of mining complexes with a high degree of modelling detail; as a result of this unified approach, non-linear relationships can easily be integrated in the optimization models - a limitation of existing deterministic and stochastic methods. Third, and a result of the previous development, a new approach is developed to model the economic value of the products sold, rather than the materials mined. Existing models and methods are limited by the assumption that each block has an economic value, hence the optimal processing stream is known a priori, and the block is treated and sold in isolation from other blocks; in some cases, this may lead to substantially undervaluing the resource. Using the new modelling approach, it is possible to evaluate the economic potential of products at the point of sale, rather than making these unrealistic assumptions at the block-level. Fourth, computationally efficient solvers are adapted and applied using metaheuristics. A combination of particle swarm optimization and a modified simulated annealing algorithm are developed to optimize various aspects of the global optimization problem; these methods have not been previously combined for mine optimization, and requires devising new methods to change designs and ensure that the optimizers do not get trapped in local optima. Finally, the performance, advantages and limitations of the models and methods are analyzed through full-field testing on real-world and large-scale examples. The results consistently reinforce the concept that it is possible to not only reduce the risk of not meeting production targets, thus guaranteeing financial forecasts are met, but also increase the net present value of the operation." --