A new methodology for the open-pit mine production scheduling problem. (December 2018) - Samavati, Mehran; Essam, Daryl; Nehring, Micah; Sarker, Ruhul
Highlights: The use of optimization techniques to address a combinatorial problem in the mining industry. The use of linear programming relaxation's solutions to generate near optimal integer solutions. Proposing a new heuristic for quickly computing a feasible solution for extremely large LP relaxations. Improving the best known solutions for a series of instances in the relevant literature. Abstract: The open pit mine production scheduling problem (OPMPSP) consists of scheduling the extraction of a mineral deposit that is broken into a number of smaller segments, or blocks, such that the net present value (NPV) of the operation is maximised. This problem has been formulated as an integer programming (IP) model, involving both knapsack and precedence constraints. However, due to the large number of blocks and precedence constraints, this model has remained impractical in real planning applications. In this paper, we propose a new method to quickly generate near optimum feasible (integer) solutions by using the fractional solutions from the linear programming (LP) relaxation of the IP model. To be applicable to real sized problems, a new heuristic that quickly computes a feasible LP solution is also proposed. Our methodology is tested on a set of both academically designed and real-world mine deposits, and shows better performance than the heuristic used to tackle the same deposits in the literature. Interestingly, the proposed methodology improves the best known solutions for the majority of the instances.