Towards sustainable mining: GHG considerate open pit long-term planning using adaptive large neighborhood search algorithm

Mine planning involves the systematic design and coordination of mineral extraction from the earth’s crust, integrating exploration, production, and various engineering considerations. With increasing emphasis on environmental responsibility, the mining industry is under pressure to incorporate environmental considerations into mine planning. This paper addresses the precedence-constrained production scheduling problem (PCPSP) within the context of green long-term mining planning, aiming to optimize extraction processes while restricting carbon emission. Given the NP hard nature of the PCPSP, this study introduces an adaptive large neighborhood search (ALNS) algorithm tailored specifically for long-term mine planning. A range of computational experiments have been carried out, including parameter tuning for the ALNS algorithm, comparisons against an exact solver, and analysis of our destroy-repair operators to determine their key elements. The efficacy of developed ALNS, evaluated using various benchmarks, reveals optimality gaps around 0.08. These results highlight the effectiveness of the proposed approach in addressing the PCPSP within mine planning and production scheduling, providing insights into improving mining operations while considering environmental concerns.