Production scheduling of open-pit mines using genetic algorithm: a case study

Abstract

ABSTRACT Open-Pit Production Scheduling (OPPS) is an NP-hard problem. In this article, Genetic Algorithm (GA) is used to encode the solutions of OPPS problem. The orebody is characterized as a three-dimensional (3D) array of blocks. Therefore, in this study, a 3D GA array is employed in the solution space of the OPPS problem to reflect the 3D feature of the real mine block model. The penalty and normalization methods are utilized for handling of the capacity and sequencing constraints, respectively. The proposed method is implemented on a Marvin orebody data set and observed a considerable improvement compared with a commercial scheduler.