How Genetic Algorithms and Cloud Processing Optimise

Automation, data analytics and optimisation are key trends in the mining industry. Doing more, and better, while expending less resources targets KPIs around efficiency and productivity. With the explosion of data, the next step is to develop an optimal level of processes and systems to harness this data to support value-in use decisions. Typically, significant amounts of resources and effort are invested to develop realistic simulation models. However, models are frequently not integrated with existing systems, and therefore are underutilised. When we consider the specialised process of blasting, integration with upstream and downstream processes is a significant driver to realise sustained improvements and value. The application of genetic algorithms and cloud computing to solving complex mining problems has advanced over the last 15 years, in particular with mine scheduling. Genetic algorithms are unique in that they support true multi-objective optimisation, utilising population-based methods to present trade-offs between multiple solutions. Secure in-cloud processing speeds up the processing, with results delivered in timeframes that are not feasible with desktop computing.