• Login
    View Item 
    •   Home
    • Theses & Dissertations
    • 2016 - Mines Theses & Dissertations
    • View Item
    •   Home
    • Theses & Dissertations
    • 2016 - Mines Theses & Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Mines RepositoryCommunitiesPublication DateAuthorsTitlesSubjectsThis CollectionPublication DateAuthorsTitlesSubjects

    My Account

    Login

    Mines Links

    Arthur Lakes LibraryColorado School of Mines

    Statistics

    Display Statistics

    Open-pit mine production scheduling under grade uncertainty

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    VanDxFAnem_mines_0052E_11167.pdf
    Size:
    4.729Mb
    Format:
    PDF
    Download
    Author
    Van-Dúnem, Ady A. D.
    Advisor
    Dagdelen, Kadri
    Johnson, Thys B.
    Date issued
    2016
    Keywords
    mine production scheduling under uncertainty
    
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/11124/170637
    Abstract
    Common challenges associated with grade uncertainty involve failing to meet decisive operational targets, which include (among others) the following: ore tonnage sent to the mill, total metal processed at the mill, blending requirements on ore feed, total waste tonnage mined, maximum allowable proportion of potentially deleterious materials (e.g., toxic elements such as arsenic). These challenges reflect, to an important extent, the uncertainty involved in defining precisely the mineral grades in an ore deposit. This has motivated a vast body of research directed at improving understanding stochastic mine planning techniques, with an aim of incorporating its tools to mine production scheduling. One popular paradigm for stochastic mine planning consists of formulating fully stochastic linear programming (SLP) models which adopt sets of realizations of the orebody to represent uncertainty regarding grades (Dimitrakopoulos et al., 2014). Since constraints must be met with total certainty, solutions from these formulations provide a decision maker with an absolute aversion to risk, i.e., one who (invariably) favors the most certain of two possible outcomes, regardless of their corresponding payoffs. Such production schedules may be too conservative in satisfying the production targets, while simultaneously producing sub-optimal results in those circumstances in which some flexibility in meeting targets exists. In a second paradigm, mine planners overcome the shortcomings of traditional production scheduling by incorporating geologic and grade uncertainty through geostatistical conditional simulations. However, this means that it is conceivable that one could also potentially benefit from any favorable development regarding previously “uncertain” domains of the ore deposit. The work undertaken in this dissertation focuses on generating production schedules that take into account grade uncertainty, as described by geostatistically simulated realizations of the ore deposit, and provide optimized production schedules that also consider the desired degree of risk in meeting the production planning outcomes. To do this, the production scheduling problem is formulated as a large-scale linear program (LP) that considers grade uncertainty as characterized by a resource block model. The large-scale LP problem is solved using an iterative decomposition algorithm whose subproblems are multi-time-period sequencing problems. At each iteration, one solves a master problem that generates a series of Lagrange multipliers (dual variables) that modify the objective function of the subproblems. In turn, the subproblem solutions modify the feasible region in the master problem and the approach is proven to converge to the optimal solution (Bienstock & Zuckerberg, 2009). The resulting LP solution is a multi-time-period mine production schedule that meets mining company’s required level of risk tolerance in mine production plans. The production scheduling formulation based on new risk-quantified linear programming models (LP) and their subsequent solutions do not only provide the risk profile of a given mine production schedule, but also allow the decision maker to define the level of acceptable risk in the mine plans generated and adopted
    Rights
    Copyright of the original work is retained by the author.
    Collections
    2016 - Mines Theses & Dissertations

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.