Open-Pit Mining Operational Planning using Multi Agent Systems

Abstract The open-pit mining operational planning problem (OPMOP) is approached by applying Multi-Agent Systems (MAS) to optimize task distribution and find the most efficient paths simultaneously. Several agents are being investigated, including several trucks with different capabilities and operating costs, as well as shovels with differing production rates and compatibility. As open pit mines have a wide range of materials, shovels are assigned to them based on their characteristics. In addition, autonomous agents must be evaluated and optimized to use minimal resources while adhering to constraints. Simulations were done to assess how the system compares to human experience by using the IoT and online data to create a successful final schedule and plan.