Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming

Abstract

Mixed Integer Programming (MIP) models are recognised as possessing the ability to optimise underground mine planning. However, MIP's use for optimising underground mine planning has often been restricted to problems of certain sizes and/or simplicity. This is because the number of variables and complex constraints in MIP formulations influences the model's ability to generate optimal results. This paper reviews optimisation studies, focusing on model reduction approaches, which employ MIP techniques for simultaneous optimisation of stope layouts and underground production scheduling. Four theories are presented to reduce the number of variables and complex constraints without comprising its mathematical integrity.