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The main cause of high-operating costs in open-pit mines is the costs of transportation. Therefore, reducing these costs could have a huge impact on overall mining efficiency and increasing profit. Meanwhile, the high cost of mining equipment, such as shovels and trucks, indicates the necessity of meticulous decision-making to find the optimal shovel-truck combination. In this paper, a new profit function for investing operations in open-pit mines is proposed using queueing theory based on a novel G/M/C//M queueing model. This function tries to maximize profit while considering budget constraints, equipment’s price, and other costs such as occupied servers, idle shovels, service in the queue, and CO 2  emission. The proposed model is solved by GAMS software for small-sized instances, and Grasshopper Optimization Algorithm (GOA) is used as a meta-heuristic approach for large-scale problems. Numerical and computational results are provided to prove the efficiency and feasibility of the model. Finally, the presented model is implemented to Chadormalu mine in Iran as a case study.

A G/M/C//M queueing model for revenue management of shovel-truck systems in an open-pit mine considering carbon emission, a case study