Development of a MIP model to maximize NPV and minimize adverse environmental impact-a heuristic approach

Block sequencing is of great importance in an open-pit mining operation. Sequencing is usually performed to maximize the net present value (NPV). Also, from the environmental viewpoint, the sequence of dumping mined materials is of significant value in the sulfide mines. The potential acid-forming (PAF) waste rocks in these mines can seriously damage the environment due to the formation of acid mine drainage (AMD). To prevent the exposition of the PAF materials, it is essential to design suitable block sequencing. For this purpose, encapsulation of the PAF rocks by non-acid forming (NAF) rocks should be considered during waste dumping. However, this method can impose unnecessary re-handling costs. This issue is due to the determination of the waste-dump sequence based on improper block sequencing obtained from the previous models with the NPV maximization strategy. In the present study, a mixed-integer programming (MIP) model is proposed for generating proper block sequencing taking into account the composition of waste rocks. The main objective of the proposed MIP model is to maximize NPV and minimize the destructive environmental effects of PAF materials dumping. The CPLEX solver was applied to solve the proposed model in small datasets. Then, an artificial bee colony (ABC) is implemented to find out optimum block sequencing and waste dumping (BSWD) on a large scale. The proposed approach was examined employing several sets of data. The obtained results were compared with those of the CPLEX solver as a benchmark. An approximate gap of 2% demonstrates the efficiency of the proposed approach.