Loading...
With MiningMath there is no complex and slow learning curve!
With MiningMath there is no complex and slow learning curve!
Destination optimization in open-pit mining is the process of deciding for each mined block the most profitable destination, such as a plant, stockpile, or waste dump. These decisions, made in real time or during planning, help maximize value by aligning material routing with processing limits, grade requirements, and financial goals.
Destination optimization is essential in open-pit mining because it directly influences the economic performance of the operation. By selecting the most profitable destination for each block, whether to processing, stockpiling, or waste, mines can maximize NPV and improve overall operational efficiency. Without a structured optimization process, mining operations risk making short-term decisions that reduce profitability and waste valuable resources.
There are several ways to approach destination optimization, ranging from simple heuristics to advanced optimization techniques. Some operations use rule-based methods or manual decisions based on cut-off grades, which are easy to apply but often fail to capture long-term value (learn more here). More advanced approaches rely on optimization algorithms, such as linear or mixed-integer programming, to evaluate multiple constraints, capacities, and economic goals over the entire mine life. The most effective solution is a global optimizer, like the one provided by MiningMath, which integrates destination decisions with long-term scheduling to maximize NPV and ensure the best use of resources.
When destination optimization is performed without a global optimizer, decisions are often made in isolation, without considering their long-term impact on the overall mine plan. This is especially common when applying cut-off grades, where choices made with limited context can conflict with broader strategic goals (learn more here). The result is often inefficient routing of materials, overloading of processing facilities, mismanagement of stockpiles, or sending marginal ore to suboptimal destinations. These issues can reduce NPV, create bottlenecks, and lead to inefficient resource use. A global optimizer helps prevent these problems by aligning all decisions with constraints, capacities, and financial objectives over the life of the mine.
MiningMath solves destination optimization through a global, single-step optimization approach that integrates destination decisions with long-term scheduling. Instead of analyzing each block or period in isolation, it evaluates all possible destinations, such as processing, stockpiles, or waste, across the entire mine life. It considers operational constraints, processing capacities, and financial objectives simultaneously to maximize NPV. This approach ensures that routing decisions are consistent with the overall mine strategy, delivering more robust and profitable outcomes than traditional local or manual methods.
With MiningMath’s single-step, optimization engine, you can uncover opportunities that manual or stepwise planning might miss. Ultimately, this engine is able to optimize resource utilization and can improve project outcomes. Transform your mine planning process by leveraging these operational constraints in the optimization process and take your mining projects to new heights of efficiency and success.
Windows 64-Bit (x86_64) - 121 MB
Hi, it's Mima here 😇 Ask me any questions!
