Applications of Integer Programming in Open Pit Mining PDF Download

Author: Christopher Fricke
Publisher:
ISBN:
Category : Integer programming
Languages : en
Pages : 510

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Author: Chris Lambert
Publisher:
ISBN:
Category : Mining engineering
Languages : en
Pages : 290

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Author: Amanda G. Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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We study new optimization-driven approaches to two engineering problems, employing techniques from integer, bilevel, stochastic, and multi-objective programming. We first present an approach to the open-pit mining truck dispatching problem that utilizes mixed-integer programming (MIP). The truck dispatching problem seeks to determine how trucks should be routed through the mine as they become available. We describe an optimization-driven approach to solving the dispatching problem in the form of a MIP model. The model is difficult to solve directly, so we present a heuristic that quickly produces high-quality feasible solutions to the model. We give computational results demonstrating the effectiveness of the proposed heuristics and several key model components. To show that our model finds solutions that meet the open-pit mining objectives while accounting for key problem components in novel ways, we embed the MIP-based dispatching policy in a discrete-event simulation of an open-pit mine. We further create two additional heuristic dispatching policies that rely on a new nonlinear rate-setting model that treats queueing at each site as an M/G/1 queue. We present a full computational study of the three policies in which we perform output analysis on key metrics of the open-pit mine simulation. We show that the MIP-based dispatching policy consistently outperforms the heuristic dispatching policies on open-pit mines with a variety of characteristics. The second problem we study is selecting metabolic network changes in cellular organisms. In this problem, enzymes are used to alter the rates at which reactions occur in cellular organisms, causing the cell to increase the output of a desired biochemical product. In existing bilevel MIP models, the lower-level cellular objective is modeled as either maximizing cellular growth or minimizing the biochemical output. We combine these perspectives with two new bilevel MIP models: a single-objective maximum productivity model and a bi-objective maximum yield and maximum growth model. We finally present two-stage stochastic extensions of both models in which we maximize the expected values of productivity, yield, and growth when the planned changes to the metabolic network are uncertain. Because the stochastic bi-objective model contains a complicating budget constraint that lacks parallel structure, we describe a heuristic that alternates between a scenario decomposition-based algorithm and allocating the budget to individual scenarios. Ultimately, we show that this methodology can be implemented to find solutions that meet the metabolic engineering objectives but which are less sensitive to uncertainty than solutions to existing models. This dissertation includes the following three supplemental data files: - A2-SimData.xlsx: data used to generate the simulation of an open-pit mine described in Chapter 3, - A3-CoreModel.xlsx: data used to generate instances of bilevel metabolic engineering models of the core network reconstruction of E. coli as described in Chapter 4, and - A3-iJR904.xlsx: data used to generate instances of bilevel metabolic engineering models of the iJR904 network reconstruction of E. coli as described in Chapter 4.

Author: Heping Xie
Publisher: CRC Press
ISBN: 1000107949
Category : Computers
Languages : en
Pages : 889

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This text covers the use of computer applications in the mineral industries, encompassing topics such as the use of computer visualization in mining systems and aspects such as ventilation and safety.

Author: Friedrich Eisenbrand
Publisher: Springer
ISBN: 3642130364
Category : Computers
Languages : en
Pages : 476

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Theidea ofa refereedconferencefor the mathematicalprogrammingcommunity was proposed by Ravi Kannan and William Pulleyblank to the Mathematical Programming Society (MPS) in the late 1980s. Thus IPCO was born, and MPS has sponsored the conference as one of its main events since IPCO I at the University of Waterloo in 1990. The conference has become the main forum for recent results in Integer Programming and Combinatorial Optimization in the non-Symposium years. This volume compiles the papers presented at IPCO XIV held June 9-11, 2010, at EPFL in Lausanne. The scope of papers considered for IPCO XIV is likely broader than at IPCO I. This is sometimes due to the wealth of new questions and directions brought from related areas. It can also be due to the successful application of “math programming” techniques to models not tra- tionally considered. In any case, the interest in IPCO is greater than ever and this is re?ected in both the number (135) and quality of the submissions. The ProgrammeCommittee with 13 memberswasalsoIPCO’slargest. We thankthe members of the committee, as well as their sub-reviewers, for their exceptional (and time-consuming) work and especially during the online committee meeting held over January. The process resulted in the selection of 34 excellent research papers which were presented in non-parallel sessions over three days in L- sanne. Unavoidably, this has meant that many excellent submissions were not able to be included.

Author: Jacob John Ricciardone
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 156

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Author: Orlando Rivera letelier
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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In scheduling problems, the goal is to assign time slots to a set of activities. In these problems, there are typically precedence constraints between activities that dictate the order in which they can be carried out and resource constraints that limit the number that can simultaneously be executed. In this thesis, we develop mixed integer programming methodologies, based on decomposition methods, for two very different classes of scheduling problems. These are the Strategic Open Pit Mine Planning Problem (SOPMP) and the Bin Packing Problem with Time Lags.Given a discretized representation of an orebody known as a block model, the SOPMP that we consider consists of defining which blocks to extract, when to extract them, and how or whether to process them, in such a way as to comply with operational constraints and maximize net present value. These problems are known to be very difficult due to the large size of real mine planning problems (eg, millions of blocks, dozens of years). They are also very important in the mining industry. Every major mining operation in the world must solve this problem, at the very least, on a yearly basis.In this thesis, we tackle the SOPMP in Chapters 2 and 3.In Chapter 2 we begin by studying a lagrangean algorithm developed by Dan Bienstock and Mark Zuckerberg (henceforth, the BZ algorithm) in 2009 for solving the LP relaxation of large instances of SOPMP. In this study we generalize the classes of problems that can be solved with the BZ algorithm, and show that it can be cast as a special type of column generation algorithm. We prove, for general classes of mixed integer programming problems, that the BZ relaxation provides a bound that lies between the LP relaxation and Dantzig-Wolfe bounds. We further develop computational speed-ups that improve the performance of the BZ algorithm in practice, and test these on a large collection of data-sets.In Chapter 3 we deal with the problem of computing integer-feasible solution to SOPMP. Using the BZ algorithm developed in Chapter 2, we develop heuristics for this. In addition, we develop pre-procesing algorithms that reduce problem size, and embed the BZ algorithm in a branch-and-cut framework that makes use of two new classes of cutting planes. When comparing the value of the heuristics to the LP relaxation bound, the average gap computed is close to 10%. However, when applying the pre-processing techniques and cutting planes, this is reduced to 1.5% at the root node. Four hours of branching further reduces this to 0.6%.In Chapter 4, the BPPTL is presented. This is a generalization of the Bin Packing Problem in which bins must be assigned to time slots, while satisfying precedence constraints with lags. Two integer programming formulations are proposed: a compact formulation that models the problem exactly, and an extended formulation that models a relaxation. For two special cases of the problem, the case with unlimited bins per period and the case with one bin per period and non-negative time lags, we strengthen the extended formulation with a special family of constraints. We propose a branch-cut-and-price (BCP) algorithm to solve this formulation, with separation of integer and fractional solutions, and a strong diving heuristic. Computational experiments confirm that the BCP algorithm outperforms solving the compact formulation with a commercial solver. Using this approach we were able to optimally solve 70% of a class of previously open instances of this problem.

Author: Amit Kumar Gorai
Publisher: CRC Press
ISBN: 1000617823
Category : Technology & Engineering
Languages : en
Pages : 405

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This book describes the fundamental and theoretical concepts of optimization algorithms in a systematic manner, along with their potential applications and implementation strategies in mining engineering. It explains basics of systems engineering, linear programming, and integer linear programming, transportation and assignment algorithms, network analysis, dynamic programming, queuing theory and their applications to mine systems. Reliability analysis of mine systems, inventory management in mines, and applications of non-linear optimization in mines are discussed as well. All the optimization algorithms are explained with suitable examples and numerical problems in each of the chapters. Features include: • Integrates operations research, reliability, and novel computerized technologies in single volume, with a modern vision of continuous improvement of mining systems. • Systematically reviews optimization methods and algorithms applied to mining systems including reliability analysis. • Gives out software-based solutions such as MATLAB®, AMPL, LINDO for the optimization problems. • All discussed algorithms are supported by examples in each chapter. • Includes case studies for performance improvement of the mine systems. This book is aimed primarily at professionals, graduate students, and researchers in mining engineering.

Author: Amit Kumar Gorai
Publisher: CRC Press
ISBN: 100061784X
Category : Technology & Engineering
Languages : en
Pages : 459

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Book Description
This book describes the fundamental and theoretical concepts of optimization algorithms in a systematic manner, along with their potential applications and implementation strategies in mining engineering. It explains basics of systems engineering, linear programming, and integer linear programming, transportation and assignment algorithms, network analysis, dynamic programming, queuing theory and their applications to mine systems. Reliability analysis of mine systems, inventory management in mines, and applications of non-linear optimization in mines are discussed as well. All the optimization algorithms are explained with suitable examples and numerical problems in each of the chapters. Features include: • Integrates operations research, reliability, and novel computerized technologies in single volume, with a modern vision of continuous improvement of mining systems. • Systematically reviews optimization methods and algorithms applied to mining systems including reliability analysis. • Gives out software-based solutions such as MATLAB®, AMPL, LINDO for the optimization problems. • All discussed algorithms are supported by examples in each chapter. • Includes case studies for performance improvement of the mine systems. This book is aimed primarily at professionals, graduate students, and researchers in mining engineering.

Author: Chotipong Somrit
Publisher:
ISBN:
Category : Integer programming
Languages : en
Pages : 304

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