Reliability based multi-objective strategic and operational mine planning through parallel meta-heuristics

通过并行元启发法进行基于可靠性的多目标战略和运营矿山规划

• 批准号: 488262-2015
• 负责人: Kumral, Mustafa
• 金额: $ 5.83万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=600699
• 关键词: Reliability; based; multi; objective; strategic

Mining is a cyclical business and experiences with periods of low prices. In Canada, mines also go deeper, which increases operation costs. These characteristics jeopardize the future of some mining operations. The suspension or termination of operations leads to increasing unemployment rate, loss of the investment and negative impact on the economies of local communities. Therefore, to stay in business, mining operations should be improved in such a way as to challenge the negative atmosphere. The advancements in the fields of computer science and operation research have an important potential to increase productivity, efficiency and profitability of mining operations. At the same time, mine planning software industry is also competitive and seeks to add new features to their variety of products to improve their product portfolio. In this scope, the proposed research aims to develop new optimization frameworks to increase the utility obtained from underground mining operations. The research will move forward from sequential to simultaneous optimization such that cut-off grade, stope layout and sequencing problems are concurrently solved to generate strategic and operational plans. The size of problem will inevitably grow. Therefore, the research will investigate various clustering, parallel and distributed computing techniques to deal with size issue. To solve the problem, a hybrid meta-heuristics using various properties of simulated annealing, genetic algorithms and tabu search will be developed. In addition to maximization of net present value, due to tactical or mine specific reasons, there could be different objectives such as recovery maximization, dilution minimization or capacity utility maximization. The problem formulation will be extended to consider multi-objective characteristics and non-dominated solutions will be generated. Hence, the decision-maker can pick up a solution suiting her/his preferences. Grade data used in underground mine planning are sparse and financial inputs depend on a series of unknown future events. Consequently, underground mine planning comprises significant degree of uncertainty. Therefore, the research will also address reliability-based optimization and risk quantification.

采矿业是一个周期性的行业，会经历低价时期。在加拿大，矿井也更深，这增加了运营成本。这些特点危及某些采矿作业的未来。业务的暂停或终止导致失业率上升、投资损失和对当地社区经济的负面影响。因此，要想继续经营，采矿业务就必须改进，以克服消极气氛。计算机科学和运筹学领域的进步对提高采矿作业的生产率、效率和盈利能力具有重要的潜力。与此同时，矿山规划软件行业也在竞争，并寻求在其各种产品中添加新功能，以改善其产品组合。在这个范围内，拟议的研究旨在开发新的优化框架，以增加从地下采矿作业中获得的效用。研究将从顺序优化推进到同时优化，从而同时解决截止品位、采场布局和排序问题，以生成战略和操作计划。问题的规模将不可避免地扩大。因此，本研究将探讨各种丛集、平行与分散式计算技术来处理大小问题。为了解决这个问题，混合元算法使用各种性质的模拟退火，遗传算法和禁忌搜索将被开发。除了净现值最大化之外，由于战术或矿山的具体原因，可能有不同的目标，如回收率最大化、稀释最小化或能力效用最大化。问题的制定将被扩展到考虑多目标特性和非支配的解决方案将产生。因此，决策者可以选择适合他/她偏好的解决方案。地下矿山规划中使用的品位数据很少，财务投入取决于一系列未知的未来事件。因此，地下矿山规划包括很大程度的不确定性。因此，该研究还将解决基于可靠性的优化和风险量化问题。