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

Abstract

ABSTRACT 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 CO2 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.